Subjects -> SOCIAL SCIENCES (Total: 1647 journals)
    - BIRTH CONTROL (22 journals)
    - CHILDREN AND YOUTH (262 journals)
    - FOLKLORE (30 journals)
    - MATRIMONY (16 journals)
    - MEN'S INTERESTS (16 journals)
    - MEN'S STUDIES (90 journals)
    - SEXUALITY (56 journals)
    - SOCIAL SCIENCES (936 journals)
    - WOMEN'S INTERESTS (44 journals)
    - WOMEN'S STUDIES (175 journals)

SOCIAL SCIENCES (936 journals)            First | 1 2 3 4 5     

Showing 801 - 136 of 136 Journals sorted alphabetically
SN Social Sciences     Hybrid Journal   (Followers: 1)
Social & Legal Studies     Hybrid Journal   (Followers: 14)
Social and Personality Psychology Compass     Hybrid Journal   (Followers: 17)
Social Behavior and Personality : An International Journal     Full-text available via subscription   (Followers: 12)
Social Choice and Welfare     Hybrid Journal   (Followers: 11)
Social Cognition     Full-text available via subscription   (Followers: 19)
Social Compass     Hybrid Journal   (Followers: 5)
Social Development & Security : Journal of Scientific Papers     Open Access  
Social Development Issues     Full-text available via subscription  
Social Education     Full-text available via subscription   (Followers: 4)
Social History Studies     Open Access   (Followers: 2)
Social Influence     Hybrid Journal   (Followers: 6)
Social Inquiry : Journal of Social Science Research     Open Access  
Social Justice Research     Hybrid Journal   (Followers: 23)
Social Landscape Journal     Open Access  
Social Philosophy and Policy     Full-text available via subscription   (Followers: 25)
Social Policy and Society     Hybrid Journal   (Followers: 134)
Social Research : An International Quarterly     Full-text available via subscription   (Followers: 5)
Social Science & Medicine     Hybrid Journal   (Followers: 98)
Social Science Computer Review     Hybrid Journal   (Followers: 13)
Social Science Japan Journal     Hybrid Journal   (Followers: 11)
Social Science Protocols     Open Access  
Social Science Research     Hybrid Journal   (Followers: 31)
Social Science Spectrum     Open Access  
Social Sciences     Open Access   (Followers: 4)
Social Sciences & Humanities Open     Open Access   (Followers: 2)
Social Sciences and Missions     Hybrid Journal   (Followers: 3)
Social Sciences in China     Hybrid Journal   (Followers: 6)
Social Semiotics     Hybrid Journal   (Followers: 7)
Social Studies and the Young Learner     Full-text available via subscription   (Followers: 2)
Social Studies of Science     Hybrid Journal   (Followers: 33)
Social Studies Research and Practice     Hybrid Journal  
Social, Humanities, and Educational Studies (SHEs) : Conference Series     Open Access  
Socialiniai tyrimai     Open Access  
Socialium : Revista Cientifica de Ciencias Sociales     Open Access  
Socialvetenskaplig tidskrift     Open Access  
Sociedad e Infancias     Open Access  
Sociedade e Cultura     Open Access  
Sociedade e Estado     Open Access   (Followers: 2)
Sociétés & Représentations     Full-text available via subscription   (Followers: 1)
Society     Open Access  
Socio     Open Access  
Socio-analysis     Full-text available via subscription   (Followers: 3)
Socio-Ecological Practice Research     Hybrid Journal  
Sociología y Tecnociencia     Open Access  
Sophia Austral     Open Access  
Soshum : Jurnal Sosial dan Humaniora     Open Access  
Sosio Didaktika : Social Science Education Journal     Open Access  
SosioHumanika: Jurnal Pendidikan Sains Sosial dan Kemanusiaan (Journal of Humanities and Social Sciences Education)     Open Access  
Soundings : An Interdisciplinary Journal     Full-text available via subscription   (Followers: 1)
South Asian Journal of Social Studies and Economics     Open Access  
Sozial Extra     Hybrid Journal   (Followers: 1)
Soziale Passagen     Hybrid Journal  
Sri Lanka Journal of Advanced Social Studies     Open Access  
Sri Lanka Journal of Social Sciences     Open Access  
Studi Magrebini : North African Studies     Full-text available via subscription  
Studia Socialia Cracoviensia     Open Access   (Followers: 1)
Studies in Asian Social Science     Open Access  
Studies in Social Justice     Open Access   (Followers: 8)
Sultan Agung Fundamental Research Journal     Open Access  
Suma de Negocios     Open Access   (Followers: 1)
Suomen Sukututkimusseuran Vuosikirja     Open Access  
Survey Research Methods     Open Access   (Followers: 3)
Sustainability     Open Access   (Followers: 22)
Sustainability : Science, Practice, & Policy     Open Access   (Followers: 2)
Symmetry     Open Access  
Symposion : Theoretical and Applied Inquiries in Philosophy and Social Sciences     Open Access  
Søkelys på arbeidslivet (Norwegian Journal of Working Life Studies)     Open Access  
Tangent     Hybrid Journal  
Tapuya : Latin American Science, Technology and Society     Open Access   (Followers: 1)
Technology transfer: innovative solutions in Social Sciences and Humanities     Open Access   (Followers: 1)
TechTrends     Hybrid Journal   (Followers: 8)
Teme : Journal of Social Sciences     Open Access  
Tempo Social     Open Access  
Teoría y Praxis     Open Access  
Textos & Contextos (Porto Alegre)     Open Access  
The Batuk     Open Access   (Followers: 14)
The Equilibrium     Open Access  
The EXceptional Parent     Full-text available via subscription  
The New Yorker     Full-text available via subscription   (Followers: 31)
The Tocqueville Review/La revue Tocqueville     Full-text available via subscription   (Followers: 3)
The Winnower     Open Access  
The Women : Annual Research Journal of Gender Studies     Open Access   (Followers: 5)
Thesis     Open Access  
Third Sector Review     Full-text available via subscription   (Followers: 3)
Tidsskrift for kjønnsforskning     Open Access  
Tidsskrift for samfunnsforskning     Open Access  
Tidsskrift for velferdsforskning     Open Access  
Tieteessä Tapahtuu     Open Access  
Tinkazos     Open Access  
Trabajos y Comunicaciones     Open Access  
Trama : Revista de Ciencias Sociales y Humanidades     Open Access  
Trans-pasando Fronteras     Open Access  
Transmodernity : Journal of Peripheral Cultural Production of the Luso-Hispanic World     Open Access   (Followers: 4)
Transmotion     Open Access   (Followers: 16)
Transtext(e)s Transcultures     Open Access  
Trayectorias Humanas Trascontinentales : TraHs     Open Access  
Trivium     Open Access   (Followers: 1)
Tulane Undergraduate Research Journal     Open Access   (Followers: 1)
Twentieth Century Communism     Full-text available via subscription   (Followers: 1)
Twenty-First Century Society: Journal of the Academy of Social Sciences     Hybrid Journal  
UC Merced Undergraduate Research Journal     Open Access  
UC Riverside Undergraduate Research Journal     Open Access  
UED Journal of Social Sciences, Humanities and Education     Open Access  
Ultima Década     Open Access  
Uluslararası Anadolu Sosyal Bilimler Dergisi / International Anatolian Journal of Social Sciences     Open Access  
Umanistica Digitale     Open Access   (Followers: 2)
Uni-pluriversidad     Open Access  
Universidad de La Habana     Open Access  
Universidad y Ciencia     Open Access  
Universidad, Escuela y Sociedad     Open Access  
Universitas Científica     Open Access  
Universitas-XXI, Revista de Ciencias Sociales y Humanas     Open Access   (Followers: 1)
University of Mauritius Research Journal     Open Access  
Universum : Revista de Humanidades y Ciencias Sociales     Open Access   (Followers: 1)
UNM Environmental Journals     Open Access  
Unoesc & Ciência - ACSA     Open Access  
VA Engage Journal     Open Access  
Variations : Revue Internationale de Théorie Critique     Open Access   (Followers: 1)
VFAST Transactions on Education and Social Sciences     Open Access  
Vilnius University Proceedings     Open Access  
Voluntas: International Journal of Voluntary and Nonprofit Organizations     Hybrid Journal   (Followers: 15)
Wani : Revista del Caribe Nicaragüense     Open Access  
War & Society     Hybrid Journal   (Followers: 27)
Weather, Climate, and Society     Hybrid Journal   (Followers: 15)
Wellbeing, Space & Society     Open Access   (Followers: 3)
Women Against Violence : An Australian Feminist Journal     Full-text available via subscription   (Followers: 15)
Workplace : A Journal for Academic Labor     Open Access   (Followers: 1)
World Journal of Social Science     Open Access  
World Journal of Social Science Research     Open Access   (Followers: 2)
Youth Studies Australia     Full-text available via subscription   (Followers: 3)
Zambia Social Science Journal     Open Access   (Followers: 2)
Zeitschrift für Medienwissenschaft     Open Access   (Followers: 2)
Œconomia     Open Access  
Вісник ДонНУЕТ. Серія. Гуманітарні науки     Open Access  
Култура / Culture     Open Access   (Followers: 1)

  First | 1 2 3 4 5     

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Journal Cover
Social Science Computer Review
Journal Prestige (SJR): 1.229
Citation Impact (citeScore): 3
Number of Followers: 13  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0894-4393 - ISSN (Online) 1552-8286
Published by Sage Publications Homepage  [1174 journals]
  • Who Says What in Which Networks: What influences Social Media Users’
           Emotional Reactions to the COVID-19 Vaccine Infodemic'

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      Authors: Aimei Yang, Shin Jieun, Hye Min Kim, Alvin Zhou, Wenlin Liu, Ke Huang-Isherwood, Eugene Jang, Jingyi Sun, Eugene Lee, Zhang Yafei, Dong Chuqin
      Abstract: Social Science Computer Review, Ahead of Print.
      This study aims to identify effective predictors that influence publics’ emotional reactions to COVID-19 vaccine misinformation as well as corrective messages. We collected a large sample of COVID-19 vaccine related misinformation and corrective messages on Facebook as well as the users’ emotional reactions (i.e., emojis) to these messages. Focusing on three clusters of features such as messages’ linguistic features, source characteristics, and messages’ network positions, we examined whether users’ reactions to misinformation and corrective information would differ. We used random forest models to identify the most salient predictors among over 70 predictors for both types of messages. Our analysis found that for misinformation, political ideology of the message source was the most salient feature that predicted anxious and enthusiastic reactions, followed by message features that highlight personal concerns and messages’ network positions. For corrective messages, while the sources’ ideology was still key to raising anxiety, the most important feature for triggering enthusiasm was the messages’ network positions and message quality.
      Citation: Social Science Computer Review
      PubDate: 2022-09-24T07:10:00Z
      DOI: 10.1177/08944393221128940
       
  • Using Google Trends Data to Learn More About Survey Participation

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      Authors: Tobias Gummer, Anne-Sophie Oehrlein
      Abstract: Social Science Computer Review, Ahead of Print.
      As response rates continue to decline, the need to learn more about the survey participation process remains an important task for survey researchers. Search engine data may be one possible source for learning about what information some potential respondents are looking up about a survey when they are making a participation decision. In the present study, we explored the potential of search engine data for learning about survey participation and how it can inform survey design decisions. We drew on freely available Google Trends (GT) data to learn about the use of Google Search with respect to our case study: participation in the Family Research and Demographic Analysis (FReDA) panel survey. Our results showed that some potential respondents were using Google Search to gather information on the FReDA survey. We also showed that the additional data obtained via GT can help survey researchers to discover topics of interest to respondents and geographically stratified search patterns. Moreover, we introduced different approaches for obtaining data via GT, discussed the challenges that come with these data, and closed with practical recommendations on how survey researchers might utilize GT data to learn about survey participation.
      Citation: Social Science Computer Review
      PubDate: 2022-09-21T02:26:14Z
      DOI: 10.1177/08944393221129179
       
  • Can Overclaiming Technique Improve Self-Assessment Tools for Digital
           Competence' The Case of DigCompSat

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      Authors: Marek Muszyński, Artur Pokropek, Jonatan Castaño-Muñoz, Riina Vuorikari
      Abstract: Social Science Computer Review, Ahead of Print.
      Digital competence is crucial for living, working and participating in current societies. Despite its huge importance, objective measurement tools for it are scarce due to its developmental difficulty. Self-assessment of digital competence seems a promising proxy of objective tests, and it additionally offers the possibility for surveying otherwise unmeasurable constructs such as attitudes and beliefs. However, self-assessment tools are burdened with validity problems, most notably response biases such as overly positive descriptions, overclaiming or careless and insufficient effort responding. In this paper, we investigate how these problems can be mitigated by using the overclaiming technique, a technique that identifies and corrects the bias variance in self-assessments. Our main result was that the use of the overclaiming technique can lead to higher reliability and validity of digital competence self-assessment tools, especially for short scales. Moreover, it allows for correcting additional spurious variance in comparison with careless responding indexes, which allows the use of both these techniques in parallel to increase the quality of data. Our results are important in providing advances in enhanced information on digital competence that can result in better lifelong learning decisions when used at the individual level and in better policy-making decisions when used at the aggregate level.
      Citation: Social Science Computer Review
      PubDate: 2022-08-31T11:58:56Z
      DOI: 10.1177/08944393221117269
       
  • A Typology of Aging Internet Users: Exploring Digital Gradations in
           Internet Skills and Uses

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      Authors: Andraž Petrovčič, Bianca C. Reisdorf, Darja Grošelj, Katja Prevodnik
      Abstract: Social Science Computer Review, Ahead of Print.
      Research suggests that older internet users are not a homogeneous group of users, as their level of digital inclusion varies widely, depending not only on their age, but also on their socio-demographic background, internet access characteristics, and the availability of social resources associated with “age-graded” life events (e.g., retirement and widowhood). This study presents a typology of internet users in late middle and late adulthood according to their levels of skills and uses and examines how socio-demographic characteristics, social networks and resources, and internet access shape differences between groups. Based on representative survey data, cluster analysis was used to identify four groups of users aged 50+: Apprehensive, Level-headed, Savvy, and Reluctant users. Three main conclusions emerge from their comparison. First, both internet skills and uses need to be considered, as more skills do not always lead to more varied use and the relationship is affected by access characteristics and proxy internet use. Second, socio-demographics remain critical in explaining gradations in digital inclusion, but their effects must be contextualized. Not all younger older adults were highly digitally engaged, so their broader life contexts need to be considered. Third, social networks and resources had little impact on aging internet users’ digital engagement.
      Citation: Social Science Computer Review
      PubDate: 2022-08-26T08:28:56Z
      DOI: 10.1177/08944393221117753
       
  • How Do Internet-Related Characteristics Affect Whether Members of a German
           Mixed-Mode Panel Switch from the Mail to the Web Mode'

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      Authors: David Bretschi, Bernd Weiß
      Abstract: Social Science Computer Review, Ahead of Print.
      In recent years, several longitudinal studies have transitioned from an interviewer-administered to a mixed-mode design, using the internet as one of the modes of data collection. However, a substantial proportion of panelists are reluctant to participate in web surveys when offered a choice in an ongoing mixed-mode panel. We still know little about the characteristics of panel members that drive them to comply with the request to complete surveys via the internet. This study aims to fill this gap by investigating how internet-related characteristics are linked to the willingness of panelists to switch from the mail mode to the web. We use data from multiple waves of the GESIS Panel, a probability-based mixed-mode panel in Germany (N = 5734). A web-push intervention motivated 28% of 1364 panelists of the mail mode to complete the survey online in a single wave and 70% of these 380 short-term switchers to switch to the web mode permanently. We measured indicators of internet use, internet skills, and attitudes toward the internet as potential mechanisms of this short-term and long-term mode switching in the two waves before the intervention. Our results suggest that internet use and internet skills affect respondents’ willingness to switch modes in a single wave. For these short-term switchers, however, none of the internet-related characteristics could explain mode switching in the long term. We also present self-reported reasons by panelists for not accepting the offer to switch modes that correspond to these findings. The results of this study can be used to develop effective push-to-web methods for longitudinal mixed-mode surveys.
      Citation: Social Science Computer Review
      PubDate: 2022-08-15T12:41:26Z
      DOI: 10.1177/08944393221117267
       
  • Privacy Calculus Theory in the Digital Government Context: The Case of
           Taiwan’s New eID Policy

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      Authors: Zong-Xian Huang, Tong-yi Huang
      Abstract: Social Science Computer Review, Ahead of Print.
      Based on the case of the national electronic identification card (New eID) policy in Taiwan, this study integrated the government’s components with a privacy calculus model to analyze factors which affect personal data disclosure intention. Partial least squares structural equation modeling (PLS-SEM) was used to analyze the survey data and explore how citizens balance benefits and risks associated with the New eID issue. The research results suggested that financial compensation, personalized services, and service compatibility can enhance cognition of privacy-related benefits of citizens, while this cognition will further increase willingness to authorize their personal data. Moreover, the impact of government elements on citizens’ willingness to authorize their personal information also has statistical backings. Citizens’ cognition of privacy-related risks, however, has no statistical effect within the model, which is contrary to findings from previous studies. The study attempted to make contributions to supplementing the connotation of an extant theoretical framework, and discussed the privacy-related questions concerning digital government.
      Citation: Social Science Computer Review
      PubDate: 2022-08-13T08:51:10Z
      DOI: 10.1177/08944393221117500
       
  • Silence in Social Media: A Multilevel Analysis of the Network Structure
           Effects on Participation Disparity in Facebook

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      Authors: Dongyoung Sohn, Yong-Suk Choi
      Abstract: Social Science Computer Review, Ahead of Print.
      Most messages on social media platforms are reportedly posted by a small number of active communicators, while the great majority of users remain silent as lurkers who read but seldom write. Despite extensive research to date, it remains unclear why such a disparity in individuals’ participation in social media exists. Drawing on the behavioral data of 15,633 Facebook users nested in 73 local networks, this study attempted to examine how the structural properties of networks give rise to the highly skewed distribution of message contributions between individual users. Multilevel statistical analyses of the data revealed that the participation disparity among individuals might be in part a function of the structural characteristics of networks in which they are embedded, suggesting that being active or silent in the social media environment is largely conditional on the surrounding network structures.
      Citation: Social Science Computer Review
      PubDate: 2022-08-13T04:20:42Z
      DOI: 10.1177/08944393221117917
       
  • EVKA—Fuzzy Modelling Based System for the Decision-Making Support of
           Community Workers

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      Authors: Michal Burda, Alice Gojová, Barbora Gřundělová, Marek Malina, Zuzana Stanková, Martin Štěpnička, Marek Vajgl
      Abstract: Social Science Computer Review, Ahead of Print.
      This article describes a unique software system for the intelligent decision-support of community workers called EVKA. Community work has been proved to be a key tool in tacking dealing social exclusion. So far, distinct approaches and expert methodologies have been developed to help community workers, especially the organization and mobilization of the community and its members through the so-called mobilization cycles. However, to the best of our knowledge, these methodologies and principles have never been implemented in an advanced software tool, and therefore their implementation has always been a matter of personal experience for each community worker. EVKA contains recent computational intelligence techniques, especially in the field of fuzzy modeling, which allow the use of expert knowledge and to use it for decision-making support purposes. This article provides readers with a detailed description of the techniques as well as their implementation.
      Citation: Social Science Computer Review
      PubDate: 2022-08-09T03:21:36Z
      DOI: 10.1177/08944393221117912
       
  • Individual and Situational Factors Influencing Active Behavior in
           Professional Video Conferences With Strangers

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      Authors: Linda-Elisabeth Reimann, Sonja Utz, Christine Anderl
      Abstract: Social Science Computer Review, Ahead of Print.
      Since the outbreak of the Covid-19 pandemic, the use of video conferences in professional settings increased rapidly. Here, we examine how individual and situational characteristics jointly predict active behavior in video conferences (i.e., activating one’s webcam, small talk, contacting other attendees) between strangers. We focus on external networking as well as proactive and reactive online networking and social anxiety as individual characteristics and investigate how these interact with social norms (operationalized as proportion of other attendees using the webcam), in predicting our outcome variable active video conference behavior. An online vignette experiment with three conditions (social norms: 25 vs. 75% of other attendees using the webcam vs. offline) was conducted to analyze the self-reported likelihood of active video conference versus active offline behavior. Regression analysis was used to test the hypotheses. Results indicate that external networking is a positive and social anxiety a negative predictor of self-reported active video conference behavior. Furthermore, the likelihood of engaging in active (video conference) behavior differed between the three scenarios, with highest values in the offline scenario and lowest in the online scenario with only 25% of other attendees using the webcam. However, no interaction effects of social norms with social anxiety were found. Overall, the findings suggest that individual differences in networking tendencies and social anxiety and social norms influence active behavior in video conferences independently.
      Citation: Social Science Computer Review
      PubDate: 2022-08-08T05:43:51Z
      DOI: 10.1177/08944393221117456
       
  • A Text Mining Approach to Determinants of Attitude Towards Syrian
           Immigration in the Turkish Twittersphere

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      Authors: Huseyin Zeyd Koytak, Muhammed Hasan Celik
      Abstract: Social Science Computer Review, Ahead of Print.
      This study uses novel deep learning-based language models to extract meaningful information from vast chunks of textual data from Twitter on the competing narratives of the recent Syrian immigration to Turkey. Our analysis identifies five main topics in the framing of Syrian immigration in Turkish Twittersphere. In this paper, we demonstrate correlational links between the timing of landmark events and change in the percent share of trends in those topics across time. We highlight two important observations: (a) Social benefit demands of natives on Twitter rose sharply with the COVID-19 pandemic, leading to ever more widespread sentiments of welfare chauvinism and (b) Patriotic feelings and the implementation of an interventionist foreign policy agenda in the immigrants’ country of origin created a relatively tolerant yet patronizing attitude towards migrants. As the COVID-19 pandemic and immigration frequently occupy the center stage in politics of immigrant-hosting societies, our research has international appeal beyond its specific geographical context.
      Citation: Social Science Computer Review
      PubDate: 2022-08-06T07:18:18Z
      DOI: 10.1177/08944393221117460
       
  • Disconnection More Problematic for Adolescent Self-Esteem than Heavy
           Social Media Use: Evidence from Access Inequalities and Restrictive Media
           Parenting in Rural America

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      Authors: Keith N. Hampton, Inyoung Shin
      Abstract: Social Science Computer Review, Ahead of Print.
      Some argue that social media use displaces time that adolescents spend with friends and family and is therefore associated with lower psychological well-being. They reason that young people who experience “disconnection,” because their parents actively restrict media use, or they have limited material access to the Internet, are better protected from psychological harm. Prior research has misspecified and exaggerated the magnitude of the relationship between screen time and adolescent psychological well-being. If the harm associated with heavy (excessive) or even average use of new media has been overstated, then the recommendation of disconnection may also be problematic. New media use is heavily integrated into youth culture and sociality, restrictive media parenting practices or digital inequalities may rob adolescents of experiences that would otherwise be protective of self-esteem. We conducted a survey of rural adolescents, who are more likely to experience disconnection at home because of a lack of physical availability of broadband, not simply affordability. Based on that survey, we find that a negative relationship between screen time and lower self-esteem is eclipsed by a more substantive, negative relationship to inequalities in material access to the Internet and restrictive mediation of media by parents. Findings show that new media use does not substantively displace time spent socializing with family and friends and in other social activities (e.g., volunteering). Omitting the supportive, indirect relationship between time on social media and self-esteem, through time spent socializing, exaggerates the negative relationship between social media use and adolescent well-being for girls, and for boys, misspecified the direction of the relationship. Adolescents, who experience heavy restrictive mediation of media by parents or have limited Internet access at home, tend to report substantively lower self-esteem than heavy users of any new media.
      Citation: Social Science Computer Review
      PubDate: 2022-08-06T06:45:10Z
      DOI: 10.1177/08944393221117466
       
  • The Real Value of Fake Internet Points: Networked Social Likes, Life
           Satisfaction, and Loneliness

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      Authors: Brandon C. Bouchillon
      Abstract: Social Science Computer Review, Ahead of Print.
      The potential for being “liked” on social networking sites to increase life satisfaction and reduce loneliness was tested in a nationally representative web survey and again over time. The initial sample was matched to U.S. Census percentages for sex, race, ethnicity, age, and region of residence in October of 2019 (N = 1250). A smaller group of respondents was surveyed in January and April of 2020, with the final wave occurring after the COVID-19 pandemic had begun (N = 665). Results suggest that having posts liked on sites including Facebook, Twitter, and Instagram contributes to life satisfaction, and life satisfaction mediates the influence of networked social likes on loneliness. Digital demonstrations of social support relate to thinking life is good, which can diminish perceived isolation. This was true in the lead-up to the pandemic, and in the midst of it, with social likes reducing loneliness by first increasing one’s sense of cognitive well-being.
      Citation: Social Science Computer Review
      PubDate: 2022-08-05T06:47:56Z
      DOI: 10.1177/08944393221117908
       
  • Falling for Social Engineering: A Qualitative Analysis of Social
           Engineering Policy Recommendations

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      Authors: Kevin F. Steinmetz, Thomas J. Holt
      Abstract: Social Science Computer Review, Ahead of Print.
      The current study examines recommendations for addressing organizational members who fall prey to social engineering as a matter of organizational policy through a qualitative analysis of interviews with organizational IT security administrators, IT security auditors, and social engineers. The results of this analysis indicate that participants had an aversion to punitive approaches to security failures. Instead, they tended to favor education as a more pragmatic and humane solution. Others argued that emphasis should be given to rewarding positive security behavior over punishing lapses. Few participants contended that there is a time and place for harsher sanctions but generally only for repeat offenders. Implications for security policy, deterrence theory, and reintegrative shaming theory are considered.
      Citation: Social Science Computer Review
      PubDate: 2022-08-05T06:12:20Z
      DOI: 10.1177/08944393221117501
       
  • Mapping the Political Landscape on Social Media Using Bibliometrics: A
           Longitudinal Co-Word Analysis on Twitter and Facebook Publications
           Published Between 2012 and 2021

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      Authors: Dragoș M. Obreja
      Abstract: Social Science Computer Review, Ahead of Print.
      Topics such as disinformation, misinformation, political polarization, and populism are frequently discussed in the social media literature. The purpose of this article is to investigate how the political emphasis on social media has evolved in the academic publications published in the last decade. Thus, using co-word analysis of the social science articles published between 2012 and 2021, which discuss politically about Facebook or Twitter (N = 3389), this article investigates whether certain major and unexpected political events—such as Donald Trump’s presidential victory and the Brexit referendum—have influenced in any way the knowledge field related to social media publications. Thus, the 2017–2021 map brings new and popular words, such as “Covid-19,” which is associated in similar clusters with words such as disinformation, fake news, and infodemic. Furthermore, the emergence of the word “Russia” places it in a common cluster with words such as bots, elections, and agenda-setting. Also, the Twitter map, unlike the Facebook one, brings a particular emphasis on Donald Trump’s activity, which appears in clusters that are similar to topics that brought him popularity on Twitter, such as: meme, migration, and refugees. Such bibliometric associations should increase policymakers’ attention to the potential use of social media as a political tool, along with designing the solutions to limit such intrusions into future political events.
      Citation: Social Science Computer Review
      PubDate: 2022-08-05T06:03:26Z
      DOI: 10.1177/08944393221117749
       
  • Is it Contagious' Does Parents’ Internet Addiction Impact Their
           Adolescents’ Internet Addiction'

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      Authors: Khansa Chemnad, Sameha Alshakhsi, Sanaa Al-Harahsheh, Azza O. Abdelmoneium, Maryam S. Al-Khalaf, Ahmed Baghdady, Raian Ali
      Abstract: Social Science Computer Review, Ahead of Print.
      Extensive research has shown various family factors such as low family cohesion, and limited parental supervision to be associated with adolescent Internet addiction (IA). There has been little discussion about the relationship between parental IA and adolescent IA. The purpose of this study was to determine whether parental IA and parental monitoring of digital technology use interpret IA in their adolescents. The current study was carried out with 168 parents of adolescents, predominantly female parents. They reported demographics and how often they monitored their adolescent’s Internet usage and responded to the Internet Addiction Diagnostic Questionnaire (IADQ) and Parental Version of Young Diagnostic Questionnaire (PYDQ). The two scales, IADQ and PYDQ, comprise of eight binary questions, each representing a symptom of IA. Multiple regression and Chi-square were used for statistical analysis. The multiple regression model showed that parents’ gender, employment status, frequency of monitoring of time spent on the Internet, and activities performed on the Internet by adolescents were not significant predictors of PYDQ. Parents’ IADQ scores and the frequency of serious arguments with their adolescents about excessive Internet use were positive and significant predictors of PYDQ. Adolescents were more likely to be dependent Internet users when their parents were also dependent Internet users. Seven of the eight IA symptoms in parents were associated with the related symptoms in adolescents. These results suggest that family counseling programs shall not only focus on dealing with adolescents but help parents demonstrate constructive and balanced digital habits and become positive role models themselves. Serious arguments on excessive Internet use predicted IA in adolescents. In light of our results, it may be beneficial for parents to play a role model in technology use and have more productive discussions with their adolescents about it. The results also signify the need for better knowledge and literacy in communicating with adolescents about excessive Internet use.
      Citation: Social Science Computer Review
      PubDate: 2022-08-05T05:17:53Z
      DOI: 10.1177/08944393221117408
       
  • The Impact of Industrial Revolution 4.0 and the Future of the Workforce: A
           Study on Malaysian IT Professionals

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      Authors: Mohd Heikal Husin, Noor Farizah Ibrahim, Nor Athiyah Abdullah, Sharifah Mashita Syed-Mohamad, Nur Hana Samsudin, Leonard Tan
      Abstract: Social Science Computer Review, Ahead of Print.
      With the advent of Industry 4.0, future workspaces are expected to evolve in tandem with technological advances in industry and education. Industry 4.0 calls for transformation and effective talent development is vital in ensuring national aspirations are achieved while eliminating redundancy and ensuring consistency. As such, this study aims to understand the impact of Industry 4.0 on computer engineering-related workforce and skills development within Multinational Companies (MNCs) to Small Medium Enterprises (SMEs) in Malaysia. In this study, online questionnaires were distributed to evaluate the current and future hiring trends. The study reveals that most of the employees have positive perceptions about the industrial current practice on Industry 4.0 and identified the prospective demands on the professions that will be affected. Five significant areas of required competencies found in this study are adaptability, soft skills, software engineering, data analytics, and technical skills. The findings provide empirical evidence about current and future employment scenarios in Malaysia concerning the possible impact of Industry 4.0 on the companies and issues involved in managing the transition to Industry 4.0. Besides, the emergent skills required by workforces that are previously unaddressed in the literature were identified. Empirical evidence from the analysis contributes to shaping the educational systems of the future and helps to proactively identify specific skills shortages at an early stage.
      Citation: Social Science Computer Review
      PubDate: 2022-08-03T07:58:46Z
      DOI: 10.1177/08944393221117268
       
  • Predicting Web Survey Breakoffs Using Machine Learning Models

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      Authors: Zeming Chen, Alexandru Cernat, Natalie Shlomo
      Abstract: Social Science Computer Review, Ahead of Print.
      Web surveys are becoming increasingly popular but tend to have more breakoffs compared to the interviewer-administered surveys. Survey breakoffs occur when respondents quit the survey partway through. The Cox survival model is commonly used to understand patterns of breakoffs. Nevertheless, there is a trend to using more data-driven models when the purpose is prediction, such as classification machine learning models. It is unclear in the breakoff literature what are the best statistical models for predicting question-level breakoffs. Additionally, there is no consensus about the treatment of time-varying question-level predictors, such as question response time and question word count. While some researchers use the current values, others aggregate the value from the beginning of the survey. This study develops and compares both survival models and classification models along with different treatments of time-varying variables. Based on the level of agreement between the predicted and actual breakoff, we find that the Cox model and gradient boosting outperform other survival models and classification models respectively. We also find that using the values of time-varying predictors concurrent to the breakoff status is more predictive of breakoff, compared to aggregating their values from the beginning of the survey, implying that respondents’ breakoff behaviour is more driven by the current response burden.
      Citation: Social Science Computer Review
      PubDate: 2022-07-11T05:55:55Z
      DOI: 10.1177/08944393221112000
       
  • Online Addictions Among Adolescents and Young Adults in Iran: The Role of
           Attachment Styles and Gender

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      Authors: Elham Salehi, Reza Fallahchai, Mark Griffiths
      Abstract: Social Science Computer Review, Ahead of Print.
      The present study aimed to investigate the role of attachment styles and gender among different online addictions (social media addiction, online gaming addiction, and internet addiction) among adolescents and young adults via an online survey. The participants comprised 943 Iranian students (440 females) selected by multi-stage cluster sampling. The survey included the nine-item form of the Problematic Internet Use Questionnaire (Laconi et al., 2019), nine-item Internet Gaming Disorder Scale-Short Form (Pontes & Griffiths, 2015), Bergen Social Media Addiction Scale (Andreassen et al., 2016), and Parent and Peer Attachment Styles Questionnaire (Gullone & Robinson, 2005). The results showed that online addictions were negatively correlated with secure attachment style, while insecure styles were positively correlated with all three types of online addiction. The results also showed that young adults were more involved in online activities, online addictive behaviors increased with age, and online gaming addiction was more prevalent among males than females. These findings indicate that individuals with a secure attachment style are less susceptible to online addictions and individuals with an insecure attachment style report more online addiction.
      Citation: Social Science Computer Review
      PubDate: 2022-07-09T01:00:19Z
      DOI: 10.1177/08944393221111242
       
  • A Survey of Blockchain Technology: Architecture, Applied Domains,
           Platforms, and Security Threats

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      Authors: Ayesha Altaf, Faiza Iqbal, Rabia Latif, Bello Musa Yakubu, Seemab Latif, Hamza Samiullah
      Abstract: Social Science Computer Review, Ahead of Print.
      Blockchain technology is at the peak of hype and contemporary research area across the world. It is a distributed ledger that keeps records of transactions with verifiable and immutable structures and continuously grows with the new block of transactions. Blockchain provides better transparency, enhanced security and privacy, and true traceability over the traditional approaches. Due to its advanced and secure features, it is being used in various fields such as trade finance, digital transactions, the Internet of Things (IoT), the healthcare industry, and energy sector. Blockchain technology has a great impact in all its applied fields with the prominent features of privacy and reliability of data and transactions. This survey intends to present the architecture of blockchain, its potential applications, and practices in different domains other than cryptocurrency along with the platform of blockchain. This paper will explore some potential benefits of blockchain and some future directions and open challenges that are expected to come in future research.
      Citation: Social Science Computer Review
      PubDate: 2022-07-06T10:04:59Z
      DOI: 10.1177/08944393221110148
       
  • Are Crime and Collective Emotion Interrelated' A “Broken Emotion”
           Conjecture from Community Twitter Posts

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      Authors: Minxuan Lan, Lin Liu, Jacob Burmeister, Weili Zhu, Hanlin Zhou, Xin Gu
      Abstract: Social Science Computer Review, Ahead of Print.
      A neighborhood’s social cohesion, referring to the emotional and social connection of people within it, tends to have an influential impact on its crime level. Traditional approaches to measuring social cohesion and collective efficacy are mostly interviews and surveys, which are usually costly in time, money, and other resources. Big social media data provides us with a new and cost-effective source of such information. We believe the combination of spatial and contextual information of geotagged Twitter posts (tweets) can gauge the residents’ collective emotions in a neighborhood. The positivity and negativity of these collective emotions may be used to approximate the collective efficacy of the community. Inspired by the broken window theory, we propose a broken emotion conjecture to explain the relationship between collective emotion and crime. To test this conjecture, we collected data on four types of crime (assaults, burglaries, robberies, and thefts) and all public geotagged tweets (N = 778,901) in Cincinnati, Ohio, USA in 2013. We extracted innovative variables from tweets’ spatial and contextual information to explain community crime and enlighten new criminology theory. Results of negative binomial models show: (1) with necessary socio-economic and land-use factors controlled, the more negative the collective emotion of a neighborhood, the more the crime (except for theft); (2) however, the positivity of the collective emotion of a neighborhood does not have any statistically significant influence on crime. These correspond well with signal detection theory in psychology. The proposed broken emotion conjecture is supported with data from Cincinnati and its general applicability should be tested in other regions.
      Citation: Social Science Computer Review
      PubDate: 2022-07-06T01:54:06Z
      DOI: 10.1177/08944393221113210
       
  • Effectiveness of WhatsApp for Measuring Migration in Follow-Up Phone
           Surveys. Lessons from a Mode Experiment in Two Low-Income Countries during
           COVID Contact Restrictions

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      Authors: Felix Ndashimye, Oumarou Hebie, Jasper Tjaden
      Abstract: Social Science Computer Review, Ahead of Print.
      Phone surveys have increasingly become important data collection tools in developing countries, particularly in the context of sudden contact restrictions due to the COVID-19 pandemic. So far, there is limited evidence regarding the potential of the messenger service WhatsApp for remote data collection despite its large global coverage and expanding membership. WhatsApp may offer advantages in terms of reducing panel attrition and cutting survey costs. WhatsApp may offer additional benefits to migration scholars interested in cross-border migration behavior which is notoriously difficult to measure using conventional face-to-face surveys. In this field experiment, we compared the response rates between WhatsApp and interactive voice response (IVR) modes using a sample of 8446 contacts in Senegal and Guinea. At 12%, WhatsApp survey response rates were nearly eight percentage points lower than IVR survey response rates. However, WhatsApp offers higher survey completion rates, substantially lower costs and does not introduce more sample selection bias compared to IVR. We discuss the potential of WhatsApp surveys in low-income contexts and provide practical recommendations for field implementation.
      Citation: Social Science Computer Review
      PubDate: 2022-07-04T03:57:56Z
      DOI: 10.1177/08944393221111340
       
  • Virtually Enhancing Public Engagement During the Pandemic: Measuring the
           Impact of Virtual Reality Powered Immersive Videos on Corporate Social
           Responsibility Communication

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      Authors: Yang Cheng, Yuan Wang, Wen Zhao, Kaijie Zhang, Xinyi Cai, Hua Jiang
      Abstract: Social Science Computer Review, Ahead of Print.
      Many companies have applied virtual reality (VR), a new and popular technology, to their corporate social responsibility (CSR) activities. This study examines how 360-degree VR-powered videos might further enhance consumers’ engagement in CSR activities and facilitate business outcomes during a crisis setting. The researchers conducted an online survey study, during the coronavirus (COVID-19) pandemic, with 1422 representative U.S. residents and applied the structural equation modeling for data analysis. Results indicated that the four categories of gratifications-sought (i.e., being there, enhancement, interaction, and fun) on 360-degree VR-powered videos could all positively influence CSR engagement; in contrast, CSR skepticism would reduce such engagement online. Corporate social responsibility engagement further improved the organization-public relationships (OPRs) and ultimately influenced consumers’ word-of-mouth toward the company. Theoretical and practical implications of these findings were discussed.
      Citation: Social Science Computer Review
      PubDate: 2022-07-02T04:04:31Z
      DOI: 10.1177/08944393221111482
       
  • How Different Categories of Gamified Stimuli Affect Massive Open Online
           Courses Continuance Intention and Learning Performance' Mediating
           Roles of Internal Experiences

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      Authors: Yung-Ming Cheng
      Abstract: Social Science Computer Review, Ahead of Print.
      Drawing on gamification literature, this study develops a research model to examine whether gamification features as environmental stimulus antecedents to learners’ organismic experiences in using massive open online courses (MOOCs) can affect their response on MOOCs and learning outcomes. The proposed research framework, rooted in the stimulus-organism-response model, provides a strong foundation for understanding these hypothesized relationships. Sample data for this study were collected from learners who had experience in taking the gamified MOOCs provided by the MOOC platform launched by a well-known university in Taiwan, and 307 usable questionnaires were analyzed using structural equation modeling. This study verified that three types of gamification features including achievement-related gamification features, immersion-related gamification features, and social interaction-related gamification features positively influenced learners’ internal experiences in using MOOCs (i.e., cognitive involvement, flow experience, and social presence), which jointly expounded their continuance intention of MOOCs, and this in turn enhanced their perceived impact on learning. Overall, this study’s results offered enough evidence to strongly support all of the hypothesized links and the research model. Besides, the results of the mediation analysis confirmed that learners’ internal experiences and continuance intention of MOOCs fully mediated the effects of their perceived gamification features on perceived impact on learning.
      Citation: Social Science Computer Review
      PubDate: 2022-07-01T09:26:39Z
      DOI: 10.1177/08944393221111928
       
  • Data as a Weapon: The Evolution of Hong Kong Protesters’ Doxing
           Strategies

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      Authors: Yao-Tai Li, Katherine Whitworth
      Abstract: Social Science Computer Review, Ahead of Print.
      In Hong Kong’s social unrest of 2019, protesters adopted a variety of strategies to express their demands, including demonstrations on the street, political consumerism, and vandalizing stores of retailers perceived to be ideologically opposed to the movement, among others. When the Hong Kong government began to more forcefully suppress and monitor the protest, data became a contentious object as well as a weapon in the repertoire of political struggle. Taking the protesters’ collective initiative of doxing the policemen and their families as an example, this article examines protesters’ engagement with data during the 2019 Hong Kong Anti-ELAB Movement. Specifically, we explore how movement participants adapted doxing practices in response to shifts in the political opportunity structure namely the passage of the National Security Law 2020 (NSL). This article investigates how the discourses, targets, strategies, and sentiments within the doxing changed following the introduction of the NSL. It also discusses the meanings and challenges of data activism and the contentious nature of doxing under different political opportunity structures.
      Citation: Social Science Computer Review
      PubDate: 2022-06-27T10:52:44Z
      DOI: 10.1177/08944393221111240
       
  • Disclosing Personal Information in mHealth Apps. Testing the Role of
           Privacy Attitudes, App Habits, and Social Norm Cues

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      Authors: Leyla Dogruel, Sven Joeckel, Jakob Henke
      Abstract: Social Science Computer Review, Ahead of Print.
      Communication privacy research has employed a plethora of theoretical approaches to explain the information disclosing behavior of users. To explain information disclosure intentions in mHealth apps, this article integrates the attitude-behavior model of privacy decisions with approaches on the role of heuristics and the impact of habitual app use. Specifically, we examine the relationship between privacy attitudes, privacy concerns, app habits, and social norm cues with the intention to disclose three types of information (personal, budget, health) in two types of mHealth apps. Testing our model in an online survey including an experimental manipulation of social norm cue strength (high/ medium/ low) among N = 475 smartphone users, our findings underline the importance of privacy attitudes for the intention to disclose information, but also point out the influence of app habits and the role of subjective evaluations of social norm cues.
      Citation: Social Science Computer Review
      PubDate: 2022-06-17T12:00:02Z
      DOI: 10.1177/08944393221108820
       
  • Loneliness and Anxiety Among Chinese Medical Students: The Mediating Role
           of Mobile Phone Addiction and the Moderating Role of Gender

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      Authors: Yucong Diao, Ziyi Feng, Hongfei Ma, Minghui Liu, Shuang Zhao, Meijun Long, Hui Wu, Yang Wang
      Abstract: Social Science Computer Review, Ahead of Print.
      The purpose of this study was to explore the relationship between loneliness and anxiety, and the mediating role of mobile phone addiction in this relationship, and whether this mediating role was moderated by gender among Chinese medical students. A cross-sectional study was conducted on March and April 2021 in Shenyang city of China. In total, 595 medical students were surveyed to complete an online questionnaire including demographic variables, mobile phone usage information, loneliness, mobile phone addiction, and anxiety, and 553 samples were effective for the final analyses. SPSS macro PROCESS was performed to test the mediating effect of mobile phone addiction and the moderating effect of gender. Our findings showed that loneliness was positively associated with anxiety, and mobile phone addiction was a partial mediator in this relationship. In addition, gender was found to moderate the indirect effect of loneliness on anxiety through mobile phone addiction. The effect of mobile phone addiction on anxiety was greater for boys than girls. This study illustrated that students with a higher level of loneliness would be more likely to develop anxiety directly and indirectly. Educational professionals should pay special attention to medical students who felt lonely or addicted to mobile phones, particularly boys.
      Citation: Social Science Computer Review
      PubDate: 2022-06-08T05:44:55Z
      DOI: 10.1177/08944393221106934
       
  • Using Double Machine Learning to Understand Nonresponse in the Recruitment
           of a Mixed-Mode Online Panel

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      Authors: Barbara Felderer, Jannis Kueck, Martin Spindler
      Abstract: Social Science Computer Review, Ahead of Print.
      Survey scientists increasingly face the problem of high-dimensionality in their research as digitization makes it much easier to construct high-dimensional (or “big”) data sets through tools such as online surveys and mobile applications. Machine learning methods are able to handle such data, and they have been successfully applied to solve predictive problems. However, in many situations, survey statisticians want to learn about causal relationships to draw conclusions and be able to transfer the findings of one survey to another. Standard machine learning methods provide biased estimates of such relationships. We introduce into survey statistics the double machine learning approach, which gives approximately unbiased estimators of parameters of interest, and show how it can be used to analyze survey nonresponse in a high-dimensional panel setting. The double machine learning approach here assumes unconfoundedness of variables as its identification strategy. In high-dimensional settings, where the number of potential confounders to include in the model is too large, the double machine learning approach secures valid inference by selecting the relevant confounding variables.
      Citation: Social Science Computer Review
      PubDate: 2022-06-08T04:36:29Z
      DOI: 10.1177/08944393221095194
       
  • A Deeper Dive into the Digital Divide: Reducing Coverage Bias in Internet
           Surveys

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      Authors: David Dutwin, Trent D. Buskirk
      Abstract: Social Science Computer Review, Ahead of Print.
      Survey research is increasingly turning to online research and as a consequence, sampling only, or disproportionately from, households with internet access. While the percentage of non-internet households has declined, it persists at about one in ten households. This raises the question of coverage error and bias, and whether there is an approach to reduce possible biases in internet-only samples. We processed nearly 5000 variables from over a dozen major public and private datasets to assess the extent of the bias. Finding substantive differences, we then applied a series of data-reducing techniques to arrive at 38 variables that independently skew across internet and non-internet populations. We then developed and fielded a survey of these metrics to assess which dozen or less could be used to construct an efficient propensity model to reduce bias in internet-only samples. Our analyses revealed that many variables noted in prior research are important predictors of non-internet use, but also identified others. Our final propensity model of 10 variables was highly effective, reducing bias significantly. Many variables tested had bias reduced fourfold. Contributions: Prior research has not investigated the digital divide from a wide array of public datasets, nor done enough to consider the bias inherent in internet users-only samples. Our novel random-forest approach and subsequent survey of key candidate variables controlled for correlations among the variables in identifying the most important variables across multiple datasets. Our coding of 542 significant predictors of internet use contributes to the sociological understanding of internet access.
      Citation: Social Science Computer Review
      PubDate: 2022-05-20T11:26:55Z
      DOI: 10.1177/08944393221093467
       
  • When Does WeChat Usage Decrease Loneliness' A Panel Study Examining
           the Moderating Roles of Age and Perceived Network Supportiveness

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      Authors: Lianshan Zhang, Xiaodong Yang, Eun Hwa Jung
      Abstract: Social Science Computer Review, Ahead of Print.
      Moving beyond examining overall social networking site (SNS) use, this study examined the influence of three types of WeChat activities on loneliness, considering the moderating roles of age and perceived network supportiveness on WeChat. Results of a two-wave panel survey with Chinese WeChat users (N = 1202 at Time 1, N = 740 at Time 2) revealed that frequent directed communication, content consumption, and broadcasting on WeChat did not directly influence participants’ loneliness across age cohorts over time. However, the effects of WeChat activities on loneliness were contingent upon a user’s age. Moreover, the positive role of WeChat activities in alleviating loneliness was significant only for users who perceived higher levels of network supportiveness on WeChat. For users who perceived lower levels of network supportiveness, frequent WeChat activities led to increased loneliness over time. These findings contribute to a more nuanced understanding of the implications of mobile SNS use on well-being across generations in the longitudinal context.
      Citation: Social Science Computer Review
      PubDate: 2022-05-20T10:59:57Z
      DOI: 10.1177/08944393221103498
       
  • Inadequate Interactions and Unbalanced Power Between Scientists and the
           Public in Chinese Knowledge Sharing Network: Social Network Analysis of
           the Topic of Genetically Modified Food on Zhihu

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      Authors: Zheng Yang
      Abstract: Social Science Computer Review, Ahead of Print.
      This study takes the scientific discussion about genetically modified food on Zhihu as an example, using the method of social network analysis to explore the interactions between Chinese scientists and the public online. The findings indicate that both scientists and non-scientists are inclined to interact with users with a similar identity. Cross-group interactions seem to be hard to achieve on Zhihu. Furthermore, compared with non-scientists, scientist users tend to hold significantly stronger digital social capital than non-scientists on Zhihu. It is suggested that the knowledge sharing network has not fully achieved the goal of effectively promoting equally science dialogue in China.
      Citation: Social Science Computer Review
      PubDate: 2022-05-18T06:12:44Z
      DOI: 10.1177/08944393221087668
       
  • Using online job postings to predict key labour market indicators

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      Authors: Miroslav Štefánik, Štefan Lyócsa, Matúš Bilka
      Abstract: Social Science Computer Review, Ahead of Print.

      Citation: Social Science Computer Review
      PubDate: 2022-05-17T01:36:38Z
      DOI: 10.1177/08944393221085705
       
  • Predicting Policy: A Psycholinguistic Artificial Intelligence in the
           United Nations

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      Authors: Kimo Gandall, Juliana Chhouk, Alex Wang, Logan Knight
      Abstract: Social Science Computer Review, Ahead of Print.
      In organizational theory, institutionalists generally make predictions of corresponding context and policy outcome based on structural processes. Psychoanalytic theory, in contrast, focuses on the rhetorical framing rather than the environment of a policy for predictive outcomes. This study aims to explore the debate over policy prediction by developing a supervised machine learning model to predict for policy success and context in the United Nations (UN). Through data collected with a python web scraper on all UN meetings in the General Assembly (GA) and Security Council (SC) between 1994 and 2020, we parse motions, policies, and conflict indicators, before passing meeting records through the Linguistic Inquiry and Word Count (LIWC) psycholinguistic algorithm. Next, we build 12 different machine learning models to predict for policy passage and context using preprocessed motion and LIWC data; results demonstrate that the psychoanalytic models better predicted for both context and policy outcomes than the institutionalist models, suggesting that the classical political axiom, “actions speak louder than words,” may not be supported by the empirical evidence.
      Citation: Social Science Computer Review
      PubDate: 2022-05-16T03:17:34Z
      DOI: 10.1177/08944393221095193
       
  • Extracting Primary Emotions and Topics from the Al-Hayat Media Centre
           

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      Authors: Konstantinos E. Maragkos, Petros E. Maravelakis
      Abstract: Social Science Computer Review, Ahead of Print.
      It is well recognized that ISIS have effectively utilized several channels to disseminate their propaganda. Producing a considerable amount of unstructured data, the Al-Hayat Media Centre had a cornerstone role in the implementation of the propaganda which targeted audiences of the Western world. Although there was a considerable effort by researchers to analyse the ISIS’s online propaganda, there are very few studies which try to relate the above-mentioned material with the emotions associated with it. In this paper, we study the influence of all known issues of the Islamic State magazines, published by the Al-Hayat Media Centre, used to disseminate propaganda, and introduced ideas to audiences outside Iraq and Syria. We perform a series of natural language processing techniques, such as Emotion and Polarity Analysis using a lexicon-based approach and topic modelling with Latent Dirichlet Allocation (LDA). We extract deep insights from the terrorist corpus, including the emotions that are dominant in the text, the combination of emotions (patterns) that the magazine authors attempt to evoke to the reader, the main topics of discussions and the overall ‘feel’ and theming of the propaganda. The combination of lexicon-based emotion analysis with the topic modelling further achieves a reduction in the ‘emotion noise’ that can be observed when applying the lexicon-based approach only, making clear which the dominant emotions are. The valuable findings discussed in this paper contribute to the existing Information Warfare literature as they provide a whole new perspective in the subject of ISIS’s propaganda. The method also aims to open an interdisciplinary discussion, with applications in politics, marketing, etc.
      Citation: Social Science Computer Review
      PubDate: 2022-05-13T06:12:44Z
      DOI: 10.1177/08944393211061272
       
  • Understanding of Majority Opinion Formation in Online Environments Through
           Statistical Analysis of News, Documentary, and Comedy YouTube Channels

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      Authors: Taehyun Ha
      Abstract: Social Science Computer Review, Ahead of Print.
      Social networking services have been placed where people share opinions and information about various topics. These services allow users to express their opinions in direct (e.g., writing a comment or reply) and indirect ways (e.g., clicking a Like button). Based on commending, replying, and liking activities, users construct majority opinions in online environments. Previous studies examined perceptual and behavioral characteristics in the circumstance of majority opinions but only few of them provided how they differ depending on content types. Based on three different types of YouTube channels (news, documentary, and comedy), this study addresses how statistical properties of user opinions and majority opinions in online environments are presented differently depending on types of content. Based on the results of statistical analyses, we provide detailed properties of user activities in three types of YouTube channels and discuss several theoretical and practical implications.
      Citation: Social Science Computer Review
      PubDate: 2022-05-10T05:40:13Z
      DOI: 10.1177/08944393211043780
       
  • The Early Bird Catches the Worm! Setting a Deadline for Online Panel
           Recruitment Incentives

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      Authors: Sabine Friedel, Barbara Felderer, Ulrich Krieger, Carina Cornesse, Annelies G. Blom
      Abstract: Social Science Computer Review, Ahead of Print.
      The literature on the effects of incentives in survey research is vast and covers a diversity of survey modes. The mode of probability-based online panels, however, is still young and so is research into how to best recruit sample units into the panel. This paper sheds light on the effectiveness of a specific type of incentive in this context: a monetary incentive that is paid conditionally upon panel registration within two weeks of receiving the initial postal mail invitation. We tested early bird cash incentives in a large-scale recruitment experiment for the German Internet Panel (GIP) in 2018. We find that panel response rates are significantly higher when offering early bird cash incentives and that fieldwork progresses considerably faster, leading to fewer reminders and greater cost-effectiveness. Furthermore, sample representativeness is similarly high with or without early bird incentives.
      Citation: Social Science Computer Review
      PubDate: 2022-05-10T05:30:27Z
      DOI: 10.1177/08944393221096970
       
  • The Illicit Ecosystem of Hacking: A Longitudinal Network Analysis of
           Website Defacement Groups

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      Authors: Robert C. Perkins, Marie Ouellet, Christian J. Howell, David Maimon
      Abstract: Social Science Computer Review, Ahead of Print.
      Over the past four decades, research on hackers has widely propagated within the social sciences. Although this area of scholarship yields rich insight into the interpersonal dynamics of hackers, research on the unique ecosystems they create and inhabit is scant in comparison. The current study aims to offer a more complete assessment of hackers’ ecosystems by incorporating the group affiliations which link hackers to one another. Using 12 months of archived website defacement data containing individuals’ self-reported group affiliations alongside their hacking activities, the study reconstructs the social network of hacker groups over time. Findings reveal the illicit ecosystem to be loosely connected, yet densely clustered around a few central groups. The ecosystem also maintained its network features across the observation period with no sign of structural degradation. These findings corroborate extant research on the social environments of hackers, offer an innovative look into the illicit ecosystem of website defacers, and serve as a steppingstone to extend investigations of criminal behavior to the group-level.
      Citation: Social Science Computer Review
      PubDate: 2022-05-10T02:06:04Z
      DOI: 10.1177/08944393221097881
       
  • Political Disaffection in the Digital Age: The Use of Social Media and the
           Gap in Internal and External Efficacy

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      Authors: Pedro Fierro, Patricio Aroca, Patricio Navia
      Abstract: Social Science Computer Review, Ahead of Print.
      This work analyzes the relationship between social media use and the development of internal and external political efficacy, using five 1,650-person polls conducted in 2017–2021 in the 10 most populated municipalities of in the Valparaiso Region in Chile, a country characterized by high levels of political discontent and social protests, especially in 2019. With Structural Equation Models, we report positive impacts of different magnitudes of the civic use of social media on internal and external efficacy and no effect of the non-civic use of social media on either type of efficacy. As lower internal and external political efficacy feeds political disaffection, the differentiated use of social media can deepen the gap between engaged and disaffected citizens.
      Citation: Social Science Computer Review
      PubDate: 2022-05-06T01:47:00Z
      DOI: 10.1177/08944393221087940
       
  • Polarization of Opinions on COVID-19 Measures: Integrating Twitter and
           Survey Data

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      Authors: Markus Reiter-Haas, Beate Klösch, Markus Hadler, Elisabeth Lex
      Abstract: Social Science Computer Review, Ahead of Print.
      Polarization of public opinion is a major issue for societies, as high levels can promote adverse effects such as hostility. The present paper focuses on the polarization of opinions regarding COVID-19 prevention measures in survey data and on Twitter in the German-speaking regions of Germany, Austria, and Switzerland. The level of polarization is measured by dispersion and bimodality in the opinions based on the sentiment in Twitter data and the agreement in the survey data. Our paper, however, goes beyond existing research as we consider data from both sources separately and comparatively. For this purpose, we matched individuals’ survey responses and tweets for those respondents who shared their Twitter account information. The analyses show that vaccination is more polarizing compared to mask wearing and contact tracing in both sources, that polarization of opinions is more pronounced in the survey data compared to the Twitter data, but also that individuals’ opinions about the COVID-19 measures are consistent in both sources. We believe our findings will provide valuable insights for integrating survey data and Twitter data to investigate opinion polarization.
      Citation: Social Science Computer Review
      PubDate: 2022-05-05T04:16:54Z
      DOI: 10.1177/08944393221087662
       
  • Mechanisms Underlying Choice-Set Formation: The Case of School Choice in
           Chile

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      Authors: Catalina Canals, Spiro Maroulis, Enrique Canessa, Sergio Chaigneau, Alejandra Mizala
      Abstract: Social Science Computer Review, Ahead of Print.
      Many decisions involve selecting among many more options than an individual can effectively examine and consider. Therefore, people usually consider smaller and different “choice sets” as viable options. To better understand the processes affecting choice-set formation, we developed a computational model of how households become aware of potential choices in a context for which understanding household decision-making has important public policy implications: market-based reforms in education. In the model, households learn about the schools to which they can send their children through three mechanisms: find out about geographically proximate schools, access to publicly available information, and information gathered from interactions with other households. We calibrated the model using data from four cities in Chile, where students are not required to attend their neighborhood school. We then used the model to conduct hypothetical computational experiments that assessed how each mechanism impacted the sets of schools known to households before they make their choice (their “awareness set”). We found that the inclusion of a social interaction mechanism was crucial for producing simulated awareness sets that matched the awareness sets provided in a survey conducted by the Chilean Ministry of Education. We also found that the social interaction mechanism played the largest role in determining the quality and price range of the choices available in households’ awareness sets. Our findings highlight the importance of social interactions in a stage of decision-making before the direct impact of other individuals is typically made explicit. Moreover, it validates an approach that can be used in future models where understanding how decision-makers become aware of their options may be as important as the way they choose among them.
      Citation: Social Science Computer Review
      PubDate: 2022-05-04T06:30:10Z
      DOI: 10.1177/08944393221088659
       
  • Why Do People Choose Different Social Media Platforms' Linking Use
           Motives With Social Media Affordances and Personalities

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      Authors: Meng Chen, Altman Yuzhu Peng
      Abstract: Social Science Computer Review, Ahead of Print.
      Drawing on uses and gratifications (U&G) theory, the current research investigates how social media users exploit different media affordances to satisfy their motives and how such motives are shaped by their personalities. A cross-sectional survey among college students (N = 190) was conducted to examine their most frequently used social media platforms, use motives, and perceived media affordances. Their personalities were also assessed along the Big Five and narcissism. An exploratory factor analysis yielded five broad categories of social media use motives. Structural equation modeling results revealed that social media use motives were differentially associated with affordances and that personalities play an influential role in shaping individuals’ use motives and affordance preferences. The findings are discussed in relation to the theoretical contributions to the U&G approach as well as the practical implications to social media platform design and development.
      Citation: Social Science Computer Review
      PubDate: 2022-04-26T09:39:57Z
      DOI: 10.1177/08944393211049120
       
  • Using Machine Learning Techniques to Predict Adolescents’
           Involvement in Family Conflict

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      Authors: Silvia Lopez-Larrosa, Vanesa Sánchez-Souto, David E. Losada, Javier Parapar, Álvaro Barreiro, Anh P. Ha, Edward M. Cummings
      Abstract: Social Science Computer Review, Ahead of Print.
      Many cases of violence against children occur in homes and other close environments. Machine leaning is a novel approach that addresses important gaps in ways of examining this socially significant issue, illustrating innovative and emerging approaches for the use of computers from a psychological perspective. In this paper, we aim to use machine learning techniques to predict adolescents’ involvement in family conflict in a sample of adolescents living with their families (community adolescents) and adolescents living in residential care centers, who are temporarily separated from their families because of adverse family conditions. Participants were 251 Spanish adolescents (Mage = 15.59), of whom 167 lived in residential care and 84 lived with their families. We measured perceived interparental and family conflict, adolescents’ emotional security, emotional, cognitive, and behavioral immediate responses to analog interparental conflict (IPC), and adolescents’ sociodemographic variables (i.e., age, gender). With a prediction accuracy of 65%, our results show that adolescents in residential care are not at greater risk for involvement in family conflict compared to adolescents living with their families. Age and gender are not salient predictive variables. We could identify that responses to analog IPC, adolescents’ emotional security, triangulation in IPC, and the presence of insults or blame during family disputes predict adolescents’ involvement in family conflict. These results point to variables with a potential predictive capacity, which is relevant for research and intervention.
      Citation: Social Science Computer Review
      PubDate: 2022-04-25T12:30:48Z
      DOI: 10.1177/08944393221084064
       
  • A Distributional Semantic Online Lexicon for Linguistic Explorations of
           Societies

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      Authors: Stefan Dahlberg, Sofia Axelsson, Amaru Cuba Gyllensten, Magnus Sahlgren, Ariel Ekgren, Sören Holmberg, Jonas Andersson Schwarz
      Abstract: Social Science Computer Review, Ahead of Print.
      Linguistic Explorations of Societies (LES) is an interdisciplinary research project with scholars from the fields of political science, computer science, and computational linguistics. The overarching ambition of LES has been to contribute to the survey-based comparative scholarship by compiling and analyzing online text data within and between languages and countries. To this end, the project has developed an online semantic lexicon, which allows researchers to explore meanings and usages of words in online media across a substantial number of geo-coded languages. The lexicon covers data from approximately 140 language–country combinations and is, to our knowledge, the most extensive free research resource of its kind. Such a resource makes it possible to critically examine survey translations and identify discrepancies in order to modify and improve existing survey methodology, and its unique features further enable Internet researchers to study public debate online from a comparative perspective. In this article, we discuss the social scientific rationale for using online text data as a complement to survey data, and present the natural language processing–based methodology behind the lexicon including its underpinning theory and practical modeling. Finally, we engage in a critical reflection about the challenges of using online text data to gauge public opinion and political behavior across the world.
      Citation: Social Science Computer Review
      PubDate: 2022-04-25T09:14:43Z
      DOI: 10.1177/08944393211049774
       
  • Employment Opportunities for Applicants with Cybercrime Records: A Field
           Experiment

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      Authors: Anuschka A. E. Peelen, Steve G. A. van de Weijer, Chantal J. W. van den Berg, Eric Rutger Leukfeldt
      Abstract: Social Science Computer Review, Ahead of Print.
      Various studies have shown that convicted offenders often face difficulties in finding employment. These studies, however, only examined traditional types of crime and little is known about the job opportunities of convicted cybercrime offenders. Therefore, this study examines the influences of being convicted for a cybercrime on labour market chances in the IT sector in the Netherlands. An experiment was conducted in which fictitious job applications were sent to existing job openings between March and June 2021 (N = 300), varying for type of crime (cybercrime, property crime, no offence) and ethnic background (Dutch or Turkish). In order to test the hypotheses, logistic regression analyses were carried out to test whether differences in responses were significant. No significant differences in positive responses were found between cybercrime offenders and non-offenders, implying that cybercrime offenders do not have less labour market opportunities. Moreover, significant differences were found between Dutch and Turkish applicants. The results of this study indicate that results from previous studies on job opportunities of traditional offenders are not generalisable to cybercrime offenders. Possibly, a cybercrime record gives a positive signal of IT-skills that are useful for employees, while a criminal record for a property crime is associated with negative characteristics.
      Citation: Social Science Computer Review
      PubDate: 2022-04-22T07:12:12Z
      DOI: 10.1177/08944393221085706
       
  • Intimate Partner Violence as Reflected in Internet Search Data

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      Authors: Brit Youngmann, Elad Yom-Tov
      Abstract: Social Science Computer Review, Ahead of Print.
      Intimate partner violence (IPV) is a major public health concern with serious consequences for victims’ physical and mental health. Despite the high prevalence of IPV, describing it and detecting people suffering from it is difficult due to its sensitive nature and stigma associated with it. Existing tools for screening and tracking IPV victims are laborious, time-consuming, expensive, and require human supervision. Search engine data has previously been shown to provide insights into temporal behavioral information about millions of users who are truthful in their information seeking. Here, we present a large-scale analysis of individuals experiencing IPV providing insights into their characteristics and behavior. We extracted the queries from Bing search engine data of more than 50 thousand US-based individuals suffering from IPV. We provide insights into the differences among subpopulations of people experiencing IPV and the topics they search for. We find that approximately half of the users begin to search for IPV following an acute event (physical violence or abuse) and 20% of users actively hide their interest in IPV. Users typically begin to seek help 3 weeks after beginning to query about IPV. The topics of interest to people experience IPV include the effects of IPV, help seeking, and methods to escape from IPV. Our insights show that early cues of IPV may be difficult to detect within search queries, though even in the late stage that many IPV users are identified, interventions such as ads to guide people to safely exit violent situations could be beneficial.
      Citation: Social Science Computer Review
      PubDate: 2022-04-12T02:48:06Z
      DOI: 10.1177/08944393221084074
       
  • Messaging, Posting, and Browsing: A Mobile Experience Sampling Study
           Investigating Youth’s Social Media Use, Affective Well-Being, and
           Loneliness

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      Authors: Kathrin Karsay, Jörg Matthes, Desirée Schmuck, Sarah Ecklebe
      Abstract: Social Science Computer Review, Ahead of Print.
      Employing a mobile experience sampling design, we investigated in the present study how different types of mobile social media use relate to young individuals’ momentary affective well-being and momentary loneliness. We differentiated between three types of social media use: Messaging, posting, and browsing. Moreover, we studied fear of missing out (FoMO) as a moderating variable. We collected data from 79 middle and late adolescents (Mage = 17.55 years, SD = 1.29; 59% girls) yielding 956 momentary assessments. The results showed that messaging and posting were positively related to affective well-being, while browsing was associated with higher levels of loneliness. Furthermore, some of the relations between social media use, affective well-being, and loneliness were also moderated by FoMO. Our results highlight the need to differentiate between different types of social media use, to include individual predispositions, and to apply methods that account for daily fluctuations in psychological well-being when studying the complex relationship between youth’s mobile social media use and well-being.
      Citation: Social Science Computer Review
      PubDate: 2022-04-06T06:34:07Z
      DOI: 10.1177/08944393211058308
       
  • A Comparative Study of Bot Detection Techniques With an Application in
           Twitter Covid-19 Discourse

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      Authors: Marzia Antenore, Jose Manuel Camacho Rodriguez, Emanuele Panizzi
      Abstract: Social Science Computer Review, Ahead of Print.
      Bot Detection is crucial in a world where Online Social Networks (OSNs) play a pivotal role in our lives as public communication channels. This task becomes highly relevant in crises like the Covid-19 pandemic when there is a growing risk of proliferation of automated accounts designed to produce misinformation content. To address this issue, we first introduce a comparison between supervised Bot Detection models using Data Selection. The techniques used to develop the bot detection models use features such as the tweets’ metadata or accounts’ Digital Fingerprint. The techniques implemented in this work proved effective in detecting bots with different behaviors. Social Fingerprint-based methods have been found to be effective with bots that behave in a coordinated manner. Furthermore, all these approaches have produced excellent results compared to the Botometer v3. Second, we present and discuss a case study related to the Covid-19 pandemic that analyses the differences in the discourse between bots and humans on Twitter, a platform used worldwide to express opinions and engage in dialogue in a public arena. While bots and humans generally express themselves alike, the tweets’ content and sentiment analysis reveal some dissimilitudes, especially in tweets concerning President Trump. When the discourse switches to pandemic management by Trump, sentiment-related values display a drastic difference, showing that tweets generated by bots have a predominantly negative attitude. However, according to our findings, while automated accounts are numerous and active in discussing controversial issues, they usually do not seem to increase exposure to negative and inflammatory content for human users.
      Citation: Social Science Computer Review
      PubDate: 2022-04-06T05:11:52Z
      DOI: 10.1177/08944393211073733
       
  • Dimensions of Online Role-Playing: Anchored in the Tolkien Mythos

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      Authors: William S. Bainbridge
      Abstract: Social Science Computer Review, Ahead of Print.
      Based on close study of two multi-player games in the tradition of J. R. R. Tolkien, this study documents the complex features of modern role-playing in online virtual worlds and constructs a six-component typology of its dimensions. The Lord of the Rings: War in the North is oriented toward the popular movies based on Tolkien’s novels, and can be played by as many as three people. The Lord of the Rings Online is based directly on the novels and is massively multi-player, even one event reported here having 487 avatars simultaneously at the same virtual location. A brief sociometric analysis of thousands of online stories in Tolkien’s legendarium, observation inside 20 Tolkien Facebook groups, and references to social science published during Tolkien’s lifetime, anchor the analysis in a tradition. The six theory components interact dynamically: identity, function, connection, engagement, representation, and property. They were derived from participant observation and ethnographic methods, but also illustrated by statistics, notably censuses of avatars and their homesteads. A great number of other role-playing computer games have similar components, but often fewer and less clearly represented. Therefore, this pair in the Tolkien mythos were especially suitable for this concept-development project.
      Citation: Social Science Computer Review
      PubDate: 2022-03-31T01:38:16Z
      DOI: 10.1177/08944393211072268
       
  • A Novel iOS Data Donation Approach: Automatic Processing, Compliance, and
           Reactivity in a Longitudinal Study

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      Authors: Susanne E. Baumgartner, Sindy R. Sumter, Vladislav Petkevič, Wisnu Wiradhany
      Abstract: Social Science Computer Review, Ahead of Print.
      For social scientists who are interested in understanding smartphone-usage patterns, as well as the causes and effects of smartphone use, it is crucial to get accurate estimates of smartphone and app usage. For this reason, we present a novel data donation approach based on screen video recordings of information provided by the iOS Battery Section. In this paper, we describe the Python script that can be used to process the data automatically. Moreover, we tested accuracy of the script, feasibility of the data collection method, as well as compliance and reactivity of the approach among a sample of 93 University students who participated in a 7-day mobile diary study. The findings of the study show that the approach works well, is very feasible and that the script resulted in accurate smartphone use data. Moreover, findings show that compliance rates were rather high, and no substantial signs of reactivity to the method occurred (i.e., participants did not change their smartphone behavior substantially while participating in this study). We therefore hope that the presented approach will encourage future researchers to use this or similar approaches to gain accurate smartphone use data in an ethical way.
      Citation: Social Science Computer Review
      PubDate: 2022-03-09T12:25:55Z
      DOI: 10.1177/08944393211071068
       
  • Verification Techniques in FinTech Compared from User Perspectives

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      Authors: Jen Sheng Wang
      Abstract: Social Science Computer Review, Ahead of Print.
      FinTech, which primarily uses mobile devices and applications as promotional platforms, is on the rise, and verification techniques play an important role. This study aims to compare verification techniques for the development of FinTech. Based on the research goal, this study newly adds the three variables “perceived privacy,” “perceived trust,” and “perceived satisfaction” to extend the traditional technology acceptance model (TAM) as the analysis architecture. Second, this study applies the fuzzy analytic hierarchy process to integrate the nonfuzzy best performance as the novelty hybrid multiple-criteria decision-making (MCDM) approach. According to the above research framework, this study investigates over 400 users for a more complete comparison of verification techniques in FinTech. The outcomes first indicate that perceived usefulness is the most emphasized key objective in comparing verification techniques. It also indicates that personal information leaking should be considered and then strengthens user trust. Additionally, the biometrics verification technique would be more advantageous for evaluating and selecting target users in FinTech industries because of their high criteria scores. The objectives and criteria of this study could suggest strategies and measures to improve verification techniques in FinTech to meet user expectations.
      Citation: Social Science Computer Review
      PubDate: 2022-03-05T08:13:25Z
      DOI: 10.1177/08944393211058310
       
  • YouTube Comments on Gene-Edited Babies: What Factors Affect Diverse
           Opinions in Comments'

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      Authors: Jiaojiao Ji, Hongchao Hu, Shitong Wei
      Abstract: Social Science Computer Review, Ahead of Print.
      This study explored the factors that influence video popularity and diverse opinions in the comments of YouTube videos about gene-edited babies. 107 most viewed videos and corresponding 56,912 direct comments about gene-edited babies were collected from YouTube. We examined how the uploader characteristics, delivery styles, video tones, and video frames affect the diverse opinions measured by sentiment polarity, sentiment divergence, and the number of topics in the commentary. The sentiments and topics of comments were analyzed using IBM Watson Natural Language Understanding. We found that more effective videos are relatively longer videos from user-created channels with a large number of subscribers and presented in a neutral tone, which is more likely to provide unbiased and comprehensive knowledge about gene-edited babies. Based on our findings, suggestions were made for viewers about how to pick high-quality content, and insights were provided for content creators about how to create compelling videos.
      Citation: Social Science Computer Review
      PubDate: 2022-03-04T04:32:29Z
      DOI: 10.1177/08944393211073164
       
  • Life of the Party: Social Networks, Public Attention, and the Importance
           of Shocks in the Presidential Nomination Process

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      Authors: Elizabeth A. Stiles, Colin D. Swearingen, Linda M. Seiter
      Abstract: Social Science Computer Review, Ahead of Print.
      We examine the effects of shocks on the invisible Presidential primary in the United States. First, we build on existing models using an algorithm simulating social network shocks. Findings show that positive shocks significantly aid the lead candidate’s chances of winning in the invisible primary. Negative shocks, however, are less detrimental to a lead candidate than positive shocks are helpful, as the leader is often able to survive a negative shock and still emerge victorious. Broad empirical tests demonstrate the importance of shocks as well. Beyond the importance of shocks, findings also suggest that Presidential candidate success in the invisible primary owes more to public- than elite-driven factors.
      Citation: Social Science Computer Review
      PubDate: 2022-03-02T12:03:07Z
      DOI: 10.1177/08944393221074599
       
  • Response Times and Subjective Complexity of Food Choices: A Web-Based
           Experiment Across 3 Countries

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      Authors: Rossella Atzori, Andrea Pellegrini, Ginevra V. Lombardi, Riccardo Scarpa
      Abstract: Social Science Computer Review, Ahead of Print.
      Accurate collection of response times is one of the main advantages of web-administered stated choice experiments and it can be thought of as a behavioral indicator of cognitive effort. We use data from a food choice experiment administered across three countries and estimate a panel Mixed Multinomial Logit Model to obtain individual-specific utility weights. These are used to construct two utility-based measures of contextual choice complexity, which are combined with subjective measures of cognitive resources as well as indicators of opt-out selection. We first develop and then test hypothesized effects of complexity at the level of single choice task and choice sequence on response times. By using a log-linear random effects model with choice task response-time as dependent variable, we isolate these effects from other background variables. Results suggest that as our measures of complexity increase, so do response times and such effects are robust across the three countries. We argue that these results broadly support the validity of web-based choice surveys to measure food preference. We suggest that computers can help improve survey design by implementing algorithms to improve the overall efficiency of choice tasks design, for example, by using adaptive design algorithms that control cognitive challenges in accordance with the respondent’s predicted ability to tackle cognitive effort.
      Citation: Social Science Computer Review
      PubDate: 2022-03-02T03:52:03Z
      DOI: 10.1177/08944393211073585
       
  • Doing Research With a Gamified Survey: Reflections From Smart City
           Research

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      Authors: Emiel A. Rijshouwer, Liesbet van Zoonen
      Abstract: Social Science Computer Review, Ahead of Print.
      Corporate and government officials as well as social scientists studying smart cities are exploring gamification to help stakeholders engage with complex technological and societal issues. However, despite research addressing concerns of respondents’ engagement and the validity and reliability of the results of gamified research, there are hardly any empirical accounts of how respondent engagement, validity and reliability of results are affected by decision-making in multi-stakeholder processes of designing and producing gamified research. In this paper, we evaluate a gamified survey that we developed to do research about public perceptions and engagements with digitization and datafication in public space. We report and evaluate the ideas, discussions and decisions in the design and production of the gamified survey. These reflections offer insights into the politics of such a process and advice for other researchers considering the use of gamified research tools for examining seemingly invisible and intangible technological developments, whilst at the same time being critical of the validity and reliability of the outcomes that such a survey produced. Our analysis shows how and why pragmatism and stakeholder relations took precedence over academic and epistemological concerns. Whilst we produced a research tool that did provoke large numbers of different people to actually engage with the smart city, the resulting data were less rich than we had aimed for, and required additional, qualitative methods.
      Citation: Social Science Computer Review
      PubDate: 2022-03-01T11:52:24Z
      DOI: 10.1177/08944393211073508
       
  • Context-dependent Online Social Influence: Effect of Majority and Minority
           Comments on Posters and Lurkers

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      Authors: Young June Sah, Wei Peng
      Abstract: Social Science Computer Review, Ahead of Print.
      While participatory websites provide users with two distinctive contexts, such as posting opinions and lurking, not many studies examine how such contexts affect the ways in which users are influenced by peer opinions. In a 2 (context: posting vs. lurking) X 3 (peer-opinion composition: balanced, lopsided, or unanimous) between-subjects experiment, participants (N = 334) revealed their opinions in a public poll or in an anonymous survey. After reading a unanimous opinion in the comments, both posting and lurking groups agreed with the unanimous opinion to a greater extent than reading the balanced opinion. After reading opposing opinions of the numerical majority and the numerical minority of peer groups, posters leaned toward the majority opinion, and lurkers toward the minority opinion. Additional analyses revealed that different mechanisms governed the effects. The moderating effect of group identification and need for cognition implies that normative influence and informational influence underlies the majority effect and minority effect, respectively.
      Citation: Social Science Computer Review
      PubDate: 2022-03-01T11:11:30Z
      DOI: 10.1177/08944393211070527
       
  • Participatory Inequality Across Countries: Contacting Public Officials
           Online and Offline

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      Authors: Shelley Boulianne
      Abstract: Social Science Computer Review, Ahead of Print.
      The Internet offers low-cost ways to participate in political life, which reduces the motivation required to participate and thus potentially reduces inequalities in participation. I examine online and offline contacting of elected officials using original survey data from Canada, France, the United Kingdom, and the United States collected in 2019 and 2021. Education is a consistent positive predictor of contacting in all countries as well as both modes of contact (online and offline). Income differences are small. Younger people are more likely to contact officials, online and offline, compared to older people. Females are less likely to contact officials, online and offline, compared to males. While political interest, efficacy, online information consumption, and online group ties are believed to lead to more equity in online communication, I do not see strong differences in these variables for online and offline contacting. I conclude by discussing the implications of exclusively online contacting of officials when this form of contact is devalued by elected officials, as well as the implications of participatory inequalities with respect to influencing public policy and access to government services.
      Citation: Social Science Computer Review
      PubDate: 2022-03-01T05:55:54Z
      DOI: 10.1177/08944393211071067
       
  • A Multilevel Perspective to Social Media Influentials’ Frame
           Building Across Crises

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      Authors: Xinyan Zhao
      Abstract: Social Science Computer Review, Ahead of Print.
      Social media influentials play key roles in information creation and impact people’s crisis interpretations and behavioral intentions. Applying a multilevel perspective, this study examined how various social media influentials’ frame building was affected by crisis clusters and message characteristics. Social media influentials’ tweets were extracted from over a million tweets from eight crises. A random sample of 2,000 tweets was analyzed by content analysis. The results showed that social media influentials’ use of responsibility and topic frames was affected by both crisis-level factors (i.e., crisis origin and organization type) and message-level factors (i.e., communicative functions and types of influentials). These findings support the importance to understand the contextual factors that condition influentials' frame building on social media.
      Citation: Social Science Computer Review
      PubDate: 2022-02-28T07:58:01Z
      DOI: 10.1177/08944393211073746
       
  • Predicting Psychological Distress During the COVID-19 Pandemic: Do
           Socioeconomic Factors Matter'

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      Authors: Nan Zou Bakkeli
      Abstract: Social Science Computer Review, Ahead of Print.
      Background and purpose:The COVID-19 pandemic has posed considerable challenges to people’s mental health, and the prevalence of anxiety and depression increased substantially during the pandemic. Early detection of potential depression is crucial for timely preventive interventions; therefore, there is a need for depression prediction.Data and methods:This study was based on survey data collected from 5001 Norwegians (3001 in 2020 and 2000 in 2021). Machine learning models were used to predict depression risk and to select models with the best performance for each pandemic phase. Probability thresholds were chosen based on cost-sensitive analysis, and measures such as accuracy (ACC) and the area under the receiver operating curve (AUC) were used to evaluate the models’ performance.Results:The study found that decision tree models and regularised regressions had the best performance in both 2020 and 2021. For the 2020 predictions, the highest accuracies were obtained using gradient boosting machines (ACC = 0.72, AUC = 0.74) and random forest algorithm (ACC = 0.71, AUC = 0.75). For the 2021 predictions, the random forest (ACC = 0.76, AUC = 0.78) and elastic net regularisation (ACC = 0.76, AUC = 0.78) exhibited the best performances. Highly ranked predictors of depression that remained stable over time were self-perceived exposure risks, income, compliance with nonpharmaceutical interventions, frequency of being outdoors, contact with family and friends and work–life conflict. While epidemiological factors (having COVID symptoms or having close contact with the infected) influenced the level of psychological distress to a larger extent in the relatively early stage of pandemic, the importance of socioeconomic factors (gender, age, household type and employment status) increased substantially in the later stage.Conclusion: Machine learning models consisting of demographic, socioeconomic, behavioural and epidemiological features can be used for fast ‘first-hand’ screening to diagnose mental health problems. The models may be helpful for stakeholders and healthcare providers to provide early diagnosis and intervention, as well as to provide insight into forecasting which social groups are more vulnerable to mental illness in which social settings.
      Citation: Social Science Computer Review
      PubDate: 2022-02-28T07:51:39Z
      DOI: 10.1177/08944393211069622
       
  • Conditional Direction of Dependence Modeling: Application and
           Implementation in SPSS

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      Authors: Xintong Li, Matthew P. Martens, Wolfgang Wiedermann
      Abstract: Social Science Computer Review, Ahead of Print.
      Conditional Direction Dependence Analysis (CDDA) has recently been proposed as a statistical framework to test reverse causation (x → y vs. y → x) and potential of confounding (x ← c → y) of variable relations in linear models when moderation is present. Similar to standard DDA, CDDA assumes that the “true” predictor is a continuous, non-normal, exogenous variable. Under non-normality, a conditional causal effect of one variable does not only change means, variances, and covariances, but also the distributional shape (i.e., skewness, kurtosis, co-skewness, and co-kurtosis) of another variable given the moderator. Such distributional changes can be used to study underlying mechanisms of heterogenous causal effects. The present study introduces conditional direction of dependence modeling and presents SPSS macros to make CDDA easily accessible to applied researchers. A real-world data example from the field of gambling addiction research is used to introduce the functionality of CDDA SPSS macros. Limitations of CDDA due to violated assumptions and poor data quality are discussed. The CDDA installation package is available at no charge from www.ddaproject.com.
      Citation: Social Science Computer Review
      PubDate: 2022-02-28T07:41:24Z
      DOI: 10.1177/08944393211073168
       
  • Relationship between Cyberbullying Victimization and Non-suicidal
           Self-Injury: Roles of Basic Psychological Needs Satisfaction and
           Self-Compassion

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      Authors: Jingyu Geng, Jue Wang, Yuhui Wang, Xingchao Wang, Li Lei, Pengcheng Wang
      Abstract: Social Science Computer Review, Ahead of Print.
      Non-suicidal self-injury has been increasingly acknowledged as a health problem. However, the association of cyberbullying victimization with non-suicidal self-injury and the mechanisms connecting this link have not been sufficiently studied. Therefore, the current study aimed to test the link between cyberbullying victimization and non-suicidal self-injury and to explore the mediating roles of basic psychological needs satisfaction and the moderating role of self-compassion in this relation. A sample of 1007 senior high students participated in the current study and completed multiple questionnaires on cyberbullying victimization, basic psychological needs satisfaction, non-suicidal self-injury, and self-compassion. The bivariate correlations between variables, mediation model, and moderated mediation model were tested by correlation analysis and Model 4 and Model 8 of the PROCESS macro, respectively. The results indicated that cyberbullying victimization was significantly and positively associated with non-suicidal self-injury. Autonomy needs satisfaction mediated the relationship between cyberbullying victimization and non-suicidal self-injury. The direct effect of cyberbullying victimization on non-suicidal self-injury was alleviated by strong self-compassion. Besides, self-compassion strengthened the direct relation between cyberbullying victimization and basic psychological needs and further strengthened the indirect association of cyberbullying victimization with non-suicidal self-injury. Our study highlights the potential mechanisms underlining the relationship between cyberbullying victimization and non-suicidal self-injury, and it has important theoretical and practical implications for adolescent non-suicidal self-injury.
      Citation: Social Science Computer Review
      PubDate: 2022-02-28T04:45:09Z
      DOI: 10.1177/08944393221074602
       
  • Explaining Attitude-Consistent Exposure on Social Network Sites: The Role
           of Ideology, Political Involvement, and Network Characteristics

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      Authors: Franz Reiter, Raffael Heiss, Jörg Matthes
      Abstract: Social Science Computer Review, Ahead of Print.
      There are rising concerns that social network sites (SNS) facilitate the creation of echo chambers, in which attitude-consistent information becomes the norm while attitude-challenging information is avoided. This study aims to investigate theoretically derived predictors of attitude-consistent and attitude-challenging exposure on SNS. We theorize that three key sets of predictors may influence attitude-consistent and attitude-challenging exposure: ideology, cognitive, and behavioral indicators of political involvement, and network characteristics. In a two-wave panel study, we predict the frequency of attitude-consistent and attitude-challenging exposure as well as relative attitude-consistent exposure, measured as attitude-consistent exposure as a share of overall opinion exposure. The results demonstrate that extreme ideological positions, higher political knowledge, and low-effort political participation predicted an increase in (relative) attitude-consistent exposure. Cross-social class exposure predicted a decrease in (relative) attitude-consistent exposure. The findings challenge existing arguments that SNS may per se facilitate attitude-consistent exposure.
      Citation: Social Science Computer Review
      PubDate: 2022-02-28T02:18:03Z
      DOI: 10.1177/08944393211056224
       
  • The Sensitivity of Community Extra-Structural Features on Event Prediction
           in Dynamic Social Networks

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      Authors: Taleb Khafaei, Alireza Tavakoli Taraghi, Mehdi Hosseinzadeh, Ali Rezaee
      Abstract: Social Science Computer Review, Ahead of Print.
      A dynamic Online Social Network is a special type of evolving complex network in which changes occur over time. The structure of a community may change over time due to the relationship changes between its members or with other communities. This is known as a community event. In this paper, we discussed the effect of important individual community features and the lengths of adequate time intervals considered in the analysis of the behavior of social networks on the prediction accuracy of each event. Furthermore, we introduced the extra-structural features as global social network features to justify the relationship between the lengths of time intervals used in the model training by using the best prediction accuracy of events. We found a relationship between the scale of network dynamics and the length of time intervals for observing the spread and decomposed events. Finally, by comparing the accuracy of the model based on time interval length which investigated based on cps-value in this study and using the Event Prediction in Dynamic Social Network (EPDSN) model, the hypothesis of a reverse relationship between cps growth rate and time interval length to obtain better prediction accuracy for both the spread and decomposed events.
      Citation: Social Science Computer Review
      PubDate: 2022-02-27T01:48:58Z
      DOI: 10.1177/08944393211055813
       
  • Open Government Maturity Models: A Global Comparison

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      Authors: Ali Pirannejad, Alex Ingrams
      Abstract: Social Science Computer Review, Ahead of Print.
      During the last decade, a new approach to bureaucratic reform in the field of public administration, open government, has aimed to increase government transparency and accountability and improve participation of citizens and other stakeholders of government. In the current era of digital governance transformations, evaluating governmental efforts to become open is a central concern of politicians, policymakers, and researchers. Various global maturity models have been developed, but the majority of them focus on the technological capacities of government rather than the historic affinity of openness and democratic governance. In this study, we attempt to address this problem by conceptualizing how governments harness technology innovations and by prescribing developmental phases for open government. Using the qualitative meta-synthesis method, we compare 10 open government maturity models to find the similarities and differences between them. Finally, we present a comprehensive model which evaluates the open government initiatives holistically and includes the following six major stages: (1) an initial stage; (2) a transparency and accountability stage; (3) an open collaboration stage; (4) a platform stage; (5) a democratic open government stage; and, finally, (6) an open governance stage.
      Citation: Social Science Computer Review
      PubDate: 2022-02-26T07:47:10Z
      DOI: 10.1177/08944393211063107
       
  • Developing Fact Finders: A Mobile Game for Overcoming Intractable
           Conflicts

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      Authors: Iolie Nicolaidou, Simon Egenfeldt-Nielsen, Rok Zupančič, Sara Hajslund, Dimitra L. Milioni
      Abstract: Social Science Computer Review, Ahead of Print.
      This study describes the design of a serious game for social change (“Fact Finders”) that presents intergroup conflicts through historical inquiry and multiperspectivity. A pre-test post-test experimental design examined the game’s effect on undergraduates’ perceptions of conflicts in history. Participants included 97 Greek Cypriots (direct parties of the conflict) and 79 Slovenians (third parties of the conflict) who interacted with and evaluated the game online. Data sources included a 17-item questionnaire on perceptions of conflicts in history and gameplay learning analytics data. Findings indicated that both groups’ perceptions for historical source evaluation and understanding multiperspectivity changed significantly after the game. The game significantly changed perceptions about the constructedness of history and the ability to overcome their country’s troubled past only for direct parties of the conflict. The study provides empirical evidence demonstrating the potential value of serious games for affecting young people’s perceptions of intractable intergroup conflicts and their desire to overcome troubled pasts.
      Citation: Social Science Computer Review
      PubDate: 2022-02-26T05:41:44Z
      DOI: 10.1177/08944393211073586
       
  • Utilising a Critical Realist Lens to Conceptualise Digital Inequality: The
           Experiences of Less Well-Off Internet Users

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      Authors: Rebecca Eynon
      Abstract: Social Science Computer Review, Ahead of Print.
      This study aims to contribute to existing understandings of the relationships between social inequality and Internet use through 30 in-depth interviews with people in Britain who have digital access, are digitally competent, and use the Internet for a broad range of purposes, yet come from lower socio-economic backgrounds. Using a critical realist lens, it examines the everyday experiences and implications of using the Internet for this group. The paper explores individuals uses of the Internet, the ways people are able to exert agency using the affordances of the Internet and the structural conditions which constrain or enable what is possible for participants to achieve. The analysis provides a way to understand the complex mechanisms of agency and structure that help to explain the varied outcomes of Internet use for different individuals; and promotes a move beyond a focus on access and skills in digital inclusion policies.
      Citation: Social Science Computer Review
      PubDate: 2022-02-25T09:56:18Z
      DOI: 10.1177/08944393211069662
       
  • Partner Phubbing and Marital Satisfaction: The Mediating Roles of Marital
           Interaction and Marital Conflict

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      Authors: Xingchao Wang, Kun Zhao
      Abstract: Social Science Computer Review, Ahead of Print.
      A growing number of studies have suggested that partner phubbing is negatively associated with marital satisfaction. However, little is known about the mediating mechanisms between this relationship. The current study investigated whether marital interaction and marital conflict mediate the relationship between partner phubbing and marital satisfaction. A sample of 470 Chinese married adults completed questionnaires regarding demographics, partner phubbing, marital interaction, marital conflict, and marital satisfaction. The results suggested that (a) partner phubbing was negatively associated with marital satisfaction; (b) both marital interaction and marital conflict partially mediated the association between partner phubbing and marital satisfaction; and (c) marital interaction and marital conflict sequentially mediated the association between partner phubbing and marital satisfaction. These findings promote our understanding of how partner phubbing is associated with marital satisfaction.
      Citation: Social Science Computer Review
      PubDate: 2022-02-25T06:32:18Z
      DOI: 10.1177/08944393211072231
       
  • Beyond Algorithmic Bias: A Socio-Computational Interrogation of the Google
           Search by Image Algorithm

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      Authors: Orestis Papakyriakopoulos, Arwa M. Mboya
      Abstract: Social Science Computer Review, Ahead of Print.
      We perform a socio-computational interrogation of the google search by image algorithm, a main component of the google search engine. We audit the algorithm by presenting it with more than 40 thousands faces of all ages and more than four races and collecting and analyzing the assigned labels with the appropriate statistical tools. We find that the algorithm reproduces white male patriarchal structures, often simplifying, stereotyping and discriminating females and non-white individuals, while providing more positive descriptions of white men. By drawing from Bourdieu’s theory of cultural reproduction, we link these results to the attitudes of the algorithm’s designers, owners, and the dataset the algorithm was trained on. We further underpin the problematic nature of the algorithm by using the ethnographic practice of studying-up: We show how the algorithm places individuals at the top of the tech industry within the socio-cultural reality that they shaped, many times creating biased representations of them. We claim that the use of social-theoretic frameworks such as the above are able to contribute to improved algorithmic accountability, algorithmic impact assessment and provide additional and more critical depth in algorithmic bias and auditing studies. Based on the analysis, we discuss the scientific and design implications and provide suggestions for alternative ways to design just socio-algorithmic systems.
      Citation: Social Science Computer Review
      PubDate: 2022-02-25T01:27:35Z
      DOI: 10.1177/08944393211073169
       
  • Effects of Prosocial Video Games on Prosocial Thoughts and Prosocial
           Behaviors

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      Authors: Hua Li, Qian Zhang
      Abstract: Social Science Computer Review, Ahead of Print.
      In this study, we examined the prosocial video game (PVG) versus neutral video game (NVG) effects on children’s prosocial behaviors. The first objective is to rate and choose the PVG and NVG by 67 experts. The second objective is to test whether playing a PVG can increase prosocial thoughts and behaviors. The third objective is to test the gender effects on prosocial thoughts and behaviors. The final objective is to assess the mediation effect of prosocial thoughts on prosocial behaviors. One hundred and 76 children (50% girls; Mage = 4.89, SD = 0.79) recruited from a Chinese kindergarten participated in the 2 (Game) x 2 (Gender) factorial experiment. Half of them were randomly assigned to play a PVG or an NVG for 20 minutes. Prosocial thoughts were measured by reaction time (RT) to prosocial pictures in the Picture Decision Task (PDT), while prosocial behaviors were measured by difficulty of jigsaw chosen for the “virtual components” in the Tangram Jigsaw Task (TJT). Results were that brief exposure of children to a PVG increased their prosocial thoughts and prosocial behaviors. More precisely, boys reported higher accessibility of prosocial thoughts and more prosocial behaviors than girls. The PVG effect on prosocial behaviors was mediated by prosocial thoughts. These findings suggest that increasing PVG exposure and training prosocial thoughts were effective ways to promote the positive development of prosocial behavior during early childhood.
      Citation: Social Science Computer Review
      PubDate: 2022-02-24T04:24:12Z
      DOI: 10.1177/08944393211069599
       
  • Technology as a Social Companion' An Exploration of Individual and
           Product-Related Factors of Anthropomorphism

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      Authors: Lara Christoforakos, Sarah Diefenbach
      Abstract: Social Science Computer Review, Ahead of Print.
      From chatbots that simulate human conversation to cleaning robots with anthropomorphic appearance, humanlike designed technologies become increasingly present in our society. A growing strand of research focuses on psychological factors and motivations influencing anthropomorphism, that is, the attribution of human characteristics to non-human agents and objects. For example, studies have shown that feeling lonely can come along with attributing anthropomorphic qualities to objects; others imply that anthropomorphism might influence individuals’ social needs in return. Such an interrelation could have great societal impact, if, for example, interacting with humanlike technology would reduce the need for interpersonal interaction. Yet, the interrelation between anthropomorphism and social needs has not been studied systematically and individual as well as situational preconditions of anthropomorphism have not been specified. The present research investigates the interrelation between anthropomorphism and social needs on the example of interacting with a smartphone and highlights possible preconditions by means of two experimental studies using a 2 × 2-between-subjects-design, varying social exclusion and anthropomorphism. Our first study (N = 159) showed an overall positive correlation between the willingness to socialize and perceived anthropomorphism. Our second study (N = 236) highlighted that this relationship is especially pronounced for individuals with a high tendency to anthropomorphize, given that the product supports a humanlike perception through its appearance and design cues. In sum, results support an interrelation between social needs and anthropomorphism but also stress individual and contextual strengthening factors. Limitations, theoretical, and practical implications are discussed.
      Citation: Social Science Computer Review
      PubDate: 2022-02-24T03:16:15Z
      DOI: 10.1177/08944393211065867
       
  • Standby Ties that Mobilize: Social Media Platforms and Civic Engagement

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      Authors: Shelley Boulianne
      Abstract: Social Science Computer Review, Ahead of Print.
      Nonprofit organizations and groups depend on donations and volunteers for their survival. Digital media can help by offering a platform for making online donations and facilitating online volunteering, but also by identifying and connecting with people who are sympathetic to an organization’s mission. This article employs four-country (USA, UK, France, and Canada) representative survey data (n = 6291) to examine the use of social media for establishing connections between citizens and organizations as well as the relationship of these connections to online and offline volunteering and donating. Across all social media platforms considered (Facebook, Instagram, and Twitter), I find significant positive correlations of following nonprofits with online and offline volunteering and donating. However, Facebook has a slightly larger role, which may be attributed to its overall popularity, which can incentivize organizations’ more intense use of this platform.
      Citation: Social Science Computer Review
      PubDate: 2022-02-22T04:46:18Z
      DOI: 10.1177/08944393211067687
       
  • Networks and Selective Avoidance: How Social Media Networks Influence
           Unfriending and Other Avoidance Behaviors

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      Authors: Matthew Barnidge, Cynthia Peacock, Bumsoo Kim, Yonghwan Kim, Michael A. Xenos
      Abstract: Social Science Computer Review, Ahead of Print.
      From time to time, some social media users avoid content posted by specific people in their networks. Most research on such selective avoidance has focused on individual motivations and other psychological factors rather than on social network characteristics, and there is a need for a systematic analysis of the relationships between individuals’ social media networks and selective avoidance. This study fills that gap in the literature, drawing on theory about egocentric or personal publics. We test our predictions using data from three surveys of adults in the United States, collected just before each of the last three major national elections. Results are discussed in light of theory about the role of media technology in shaping political communication and scholarly discourse about how selective avoidance affects information flows.
      Citation: Social Science Computer Review
      PubDate: 2022-02-22T02:51:09Z
      DOI: 10.1177/08944393211069628
       
  • Gender-Related Differences in Online Comment Sections: Findings From a
           Large-Scale Content Analysis of Commenting Behavior

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      Authors: Constanze Küchler, Anke Stoll, Marc Ziegele, Teresa K. Naab
      Abstract: Social Science Computer Review, Ahead of Print.
      Comment sections below news articles are public fora in which potentially everyone can engage in equal and fair discussions on political and social issues. Yet, empirical studies have reported that many comment sections are spaces of selective participation, discrimination, and verbal abuse. The current study complements these findings by analyzing gender-related differences in participation and incivility. It uses a sample of 303,342 user comments from 14 German news media Facebook pages. We compare participation rates of female and male users as well as associations between the users’ gender, the incivility of their comments, and the incivility of the adjacent replies. To determine the incivility of the comments, we developed a Supervised Machine Learning Model (classifier) using pre-trained word embeddings and word// frequency features. The findings show that, overall, women participate less than men. Comments written by female authors are more civil than comments written by male authors. Women’s comments do not receive more uncivil replies than men’s comments and women are not punished disproportionately for communicating uncivilly. These findings contribute to the discourse on gender-related differences in online comment sections and provide insights into the dynamics of online discussions.
      Citation: Social Science Computer Review
      PubDate: 2022-02-15T06:33:11Z
      DOI: 10.1177/08944393211052042
       
  • Facebook Users’ Satisfaction and Intention to Continue Using It:
           Applying the Expectation Confirmation Model

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      Authors: Md Irfanuzzaman Khan, M. Abu Saleh
      Abstract: Social Science Computer Review, Ahead of Print.
      The use of social media for health communication has grown enormously worldwide. Whilst research concerning the potential benefits and barriers of using social media is rich and ever expanding, only a few studies looked at the fundamental reasons why social networking users continue to use Facebook for accessing health-related support groups and communicating with the healthcare professionals. Based on the expectation confirmation model (ECM), this study aims to uncover the factors that explain users’ intention to continue using Facebook for health-related matters. A sample size of 239 respondents was collected to test the proposed theoretical framework, using thestructural equation modelling technique. Our findings indicate that the most important drivers of continuance intention of Facebook are satisfaction, perceived usefulness, information quality and social support, whilst confirmation of expectation, information quality and social support are determinants of satisfaction. This study offers new insights into the domain of post-technology adoption and health communication literature. It also provides important information for healthcare providers on how to improve the effectiveness of social network-based interactions.
      Citation: Social Science Computer Review
      PubDate: 2022-02-04T03:44:48Z
      DOI: 10.1177/08944393211066584
       
  • Cybervictimization, Social, and Financial Strains Influence Internet
           Trolling Behaviors: A General Strain Theory Perspective

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      Authors: Nigel C. Wilson, Kathryn C. Seigfried-Spellar
      Abstract: Social Science Computer Review, Ahead of Print.
      Internet trolling is a form of online aggression that can have negative psychological effects on its victims. This study examines whether Internet trolling behaviors is related to general strain theory. Respondents were solicited from Mechanical Turk and completed an anonymous, Internet-based survey measuring a variety of trolling behaviors and strains (i.e., cyberbullying victimization, trolling victimization, financial strain, and social strain). Of the 259 respondents, 55% self-reported engaging in Internet trolling behaviors. Partial correlations, controlling for sex and age, suggested trolling was significantly related to cyberbullying victimization, trolling victimization, financial strain, and social strain. The hierarchical (blockwise entry) logistic regression found trolls scored higher on cyberbullying victimization, trolling victimization, and financial strain compared to non-trolls. In addition, there was a marginally significant relationship between trolling and higher scores on social strain. Men were also more likely to engage in trolling behaviors compared to women. We conclude there is a relationship between online trolling behaviors and general strain theory. Future research should consider other sources of strain and comparisons between the different types of trolling behaviors (e.g., flaming, griefing, and memorial page trolling) when examining the relationship between trolling and strains. Additional future research suggestions and study limitations are discussed.
      Citation: Social Science Computer Review
      PubDate: 2022-02-03T07:28:25Z
      DOI: 10.1177/08944393211065868
       
  • Item Nonresponse in Web Versus Other Survey Modes: A Systematic Review and
           Meta-Analysis

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      Authors: Gregor Čehovin, Michael Bosnjak, Katja Lozar Manfreda
      Abstract: Social Science Computer Review, Ahead of Print.
      Nonresponse is a fundamental issue in survey research, due to the trend of declining response rates across survey modes. This issue is particularly serious for web surveys: A recent meta-analysis found that unit nonresponse in web surveys is, on average, higher by 12 percentage points than in other modes (Daikeler et al., 2020). Although the issue of unit nonresponse in web and other survey modes has been investigated in several meta-analyses, item nonresponse has not been examined meta-analytically, a gap addressed by this paper. Are web surveys at a disadvantage compared to other survey modes in terms of item nonresponse as well' To address this question, 13 eligible experimental manuscripts reporting 23 effect sizes were identified in a comprehensive literature search. Meta-analytic findings showed that there was no statistically significant difference in the average item nonresponse rate in web versus other survey modes. However, six moderator variables were found to statistically significantly affect the relation between the survey mode and the item nonresponse rate, namely, the target population, the number of contacts, the mode to which the web survey mode was compared, the survey sponsor, the age of the survey, and the baseline item nonresponse rate of the compared mode. The main practical implication is that while web and other survey modes differ in terms of unit nonresponse (on average), item nonresponse rates in web surveys are similar compared to other modes.
      Citation: Social Science Computer Review
      PubDate: 2022-02-02T05:37:28Z
      DOI: 10.1177/08944393211056229
       
  • Less Fragmented but Highly Centralized: A Bibliometric Analysis of
           Research in Computational Social Science

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      Authors: Xiaohui Wang, Yunya Song, Youzhen Su
      Abstract: Social Science Computer Review, Ahead of Print.
      Since its inception, computational social science (CSS) has been characterized as an interdisciplinary field. Nevertheless, unlike a mature interdisciplinary field that duly integrates knowledge beyond disciplinary boundaries, CSS has arguably been fragmented into multiple lines of inquiry. Although such fragmentation has been a constant concern, limited empirical evidence exists to substantiate any degree of integration in research on CSS. To systematically map the landscape of research on CSS, we examined the dynamic topology of the bibliometric network of CSS during the past 20 years. By comparing the structure of the coupling network and the co-subject network with three prototypical network models that we simulated—the centralized model, the fragmented model, and the cohesive model—our analysis revealed that the citation networks of research on CSS are highly centralized but less fragmented than often assumed. Beyond that, a driving factor shaping the coupling network’s cohesive structure is the citation to high-impact articles. Those and other findings contribute to current understandings of the process of integration in the evolution of disciplines.
      Citation: Social Science Computer Review
      PubDate: 2022-02-02T03:34:18Z
      DOI: 10.1177/08944393211058112
       
  • Measuring Violence: A Computational Analysis of Violence and Propagation
           of Image Tweets From Political Protest

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      Authors: Luca Rossi, Christina Neumayer, Jesper Henrichsen, Lucas K. Beck
      Abstract: Social Science Computer Review, Ahead of Print.
      This research quantitatively investigates the impact of violence on the propagation of images in social media in the context of political protest. Using a computational approach, we measure the relative violence of a large set of images shared on Twitter during the protests against the G20 summit in Frankfurt am Main in 2017. This allows us to investigate if more violent content is shared more times and faster than less violent content on Twitter, and if different online communities can be characterized by the level of violence of the visual content they share. The results show that the level of violence in an image tweet does not correlate with the number of retweets and mentions it receives that the time to retweet is marginally lower for image tweets containing a high level of violence and that the level of violence in image tweets differs between communities.
      Citation: Social Science Computer Review
      PubDate: 2022-01-31T04:55:07Z
      DOI: 10.1177/08944393211055429
       
  • Connections Between Internet, Social Media News Use, and Political
           Participation in Kenya

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      Authors: Gilbert Kipkoech
      Abstract: Social Science Computer Review, Ahead of Print.
      Competing theories have been put forward about the effect of Internet and social media use for news on political engagement. Some argue that Internet use for news reduces political engagement while others suggest that it increases political participation. Similar arguments have been advanced for the effects of social media use. This study tests both claims using representative data of over 2000 Kenyans. Bivariate results show that Internet and social media use for news has a positive relationship with political participation in Kenya. After controlling for demographic variables, political orientation variables, and traditional news use, digital media use (i.e., Internet and social media use for news) shows no significant associations with political participation in Kenya.
      Citation: Social Science Computer Review
      PubDate: 2022-01-29T06:02:18Z
      DOI: 10.1177/08944393211058702
       
  • Can Twitter be a Reliable Proxy to Characterize Nation-wide Human
           Mobility' A Case Study of Spain

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      Authors: Fernando Terroso-Saenz, Andrés Muñoz, Francisco Arcas, Manuel Curado
      Abstract: Social Science Computer Review, Ahead of Print.
      In recent years, there has been an increasing interest in the exploitation of geo-tagged documents posted on Online Social Networks (OSN) for human-mobility pattern mining. These patterns can ease the development of effective and intelligent location-based systems of different scenarios. However, the validation of OSN geo-data as a reliable source for human mobility has not been fully studied in literature. Therefore, this study proposes a comprehensive comparison of a nation-scale Twitter (TWT) dataset with an official mobility study published by the Spanish Ministry of Development. Both feeds have been compared considering different variables, such as population density and spatial granularity, among others. Results show that TWT can be a reliable source for human-mobility mining but only when certain socioeconomic, temporal, and spatial factors co-occur.
      Citation: Social Science Computer Review
      PubDate: 2022-01-29T02:35:25Z
      DOI: 10.1177/08944393211071071
       
  • Breaking the Structural Reinforcement: An Agent-Based Model on Cultural
           Consumption and Social Relations

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      Authors: Qiankun Zhong, Martin Hilbert, Seth Frey
      Abstract: Social Science Computer Review, Ahead of Print.
      Theorists since Marx, Bourdieu, and DiMaggio have asked how individual choices on cultural preference interact with collective social network structure. The rise of social media in today’s communication landscape motivates us to take a closer look at the involved dynamics. We designed an agent-based model to explore how different behavioral principles for cultural choice and communicative affiliation affect (1) collective consumption patterns, (2) social segregation, and (3) resilience of the emergent dynamic during exogenous distributions. We analyze the influence of individual agency on network structure, and vice versa, by simulating agents who pursue elite or popular culture, while communicating with others based on homophily or randomness. Our method allows us to go beyond specific constellations and explore the realm of theoretically possible combinations. We then used an exogenous disturbance on elite culture cost to test the resilience of social network structure. We found that only in societies where economic factors drive cultural consumption, increased access to elite culture can lead to reorganization in the social network and reduce segregation between different social groups. This is because the disturbance on consumption provides agents opportunities to connect with other social groups and opens a window for social mixing. We end by discussing how our model allows us to inform a diverse set of empirical research questions, including the cultural markets of social media, the digital divide, and the split between free misinformation and established news outlets.
      Citation: Social Science Computer Review
      PubDate: 2022-01-29T01:06:35Z
      DOI: 10.1177/08944393211056501
       
  • Exploring Employees’ After-Hour Work Communication on Public Social
           Media: Antecedents and Outcomes

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      Authors: Cen April Yue
      Abstract: Social Science Computer Review, Ahead of Print.
      This study focused on employees’ work-related social media use outside regular work hours and explored its antecedents and outcomes. Drawing from boundary theory and employee-organization relationship management literature, this study investigated how employees’ preference for work–family segmentation and quality employee-organization relationship affected employees’ work-related social media use. In addition, informed by the effort-recovery model, the current study proposed low psychological detachment from work and high work–family conflict as outcomes of work-related social media use. Through an online survey with 815 employees in the United States, findings of the study supported the proposed antecedents and outcomes. Specifically, employees with a stronger preference for segmenting the work from the home domain engaged less in work-related social media use, and in turn, experienced higher levels of psychological detachment from work and less work–family conflict. On the other hand, those who had high-quality relationships with their organizations reported higher engagement levels in work-related social media, which resulted in lower psychological detachment from work and higher work–family conflict.
      Citation: Social Science Computer Review
      PubDate: 2022-01-20T12:32:15Z
      DOI: 10.1177/08944393211055322
       
  • Language Analysis and the Role of Facebook Hashtags in Pakistan

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      Authors: Umbreen Tariq
      Abstract: Social Science Computer Review, Ahead of Print.
      Over the past few years, online hashtags have gained tremendous fame mainly because of two reasons: first, as digital information trackers and second, as short and spontaneous communication tags. The present study aims to explore language factors in three types of Facebook hashtags, that is, long, short, and multiple mixed. It further investigates each factor’s role in online communication by performing an in-depth examination through activities and close-ended questions. First, it identifies factors through the writing activities where participants wrote different hashtags with their intention behind each hashtag. It follows interpretation activities in which other participants wrote their interpretations about the already written hashtags. Further, a 5-point Likert scale questionnaire was developed to note participants’ opinions about hashtags which were evaluated by the SPSS factor analysis test. Results of the study are divided into three sections and showed that lack of adequate vocabulary and lower casing is an important factor affecting digital communication in Pakistan. It is also suggested that teachers should play their part to improve informal writing and digital literacy in Pakistan.
      Citation: Social Science Computer Review
      PubDate: 2022-01-17T10:49:29Z
      DOI: 10.1177/08944393211065866
       
  • Politics Go “Viral”: A Computational Text Analysis of the Public
           Attribution and Attitude Regarding the COVID-19 Crisis and Governmental
           Responses on Twitter

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      Authors: Weilu Zhang, Lingshu Hu, Jihye Park
      Abstract: Social Science Computer Review, Ahead of Print.
      The U.S. confronts an unprecedented public health crisis, the COVID-19 pandemic, in the presidential election year in 2020. In such a compound situation, a real-time dynamic examination of how the general public ascribe the crisis responsibilities taking account to their political ideologies is helpful for developing effective strategies to manage the crisis and diminish hostility toward particular groups caused by polarization. Social media, such as Twitter, provide platforms for the public’s COVID-related discourse to form, accumulate, and visibly present. Meanwhile, those features also make social media a window to monitor the public responses in real-time. This research conducted a computational text analysis of 2,918,376 tweets sent by 829,686 different U.S. users regarding COVID-19 from January 24 to May 25, 2020. Results indicate that the public’s crisis attribution and attitude toward governmental crisis responses are driven by their political identities. One crisis factor identified by this study (i.e., threat level) also affects the public’s attribution and attitude polarization. Additionally, we note that pandemic fatigue was identified in our findings as early as in March 2020. This study has theoretical, practical, and methodological implications informing further health communication in a heated political environment.
      Citation: Social Science Computer Review
      PubDate: 2022-01-17T08:12:54Z
      DOI: 10.1177/08944393211053743
       
  • Enhancing Participation in Probability-Based Online Panels: Two Incentive
           Experiments and Their Effects on Response and Panel Recruitment

    • Free pre-print version: Loading...

      Authors: Nils Witte, Ines Schaurer, Jette Schröder, Jean Philippe Décieux, Andreas Ette
      Abstract: Social Science Computer Review, Ahead of Print.
      This article investigates how mail-based online panel recruitment can be facilitated through incentives. The analysis relies on two incentive experiments and their effects on panel recruitment, and the intermediate participation in the recruitment survey. The experiments were implemented in the context of the German Emigration and Remigration Panel Study and encompass two samples of randomly sampled persons. Tested incentives include a conditional lottery, conditional monetary incentives, and the combination of unconditional money-in-hand with conditional monetary incentives. For an encompassing evaluation of the link between incentives and panel recruitment, the article further assesses the incentives’ implications for demographic composition and panel recruitment unit costs. Multivariate analysis indicates that low combined incentives (€5/€5) or, where unconditional disbursement is unfeasible, high conditional incentives (€20) are most effective in enhancing panel participation. In terms of demographic bias, low combined incentives (€5/€5) and €10 conditional incentives are the favored options. The budget options from the perspective of panel recruitment include the lottery and the €10 conditional incentive which break-even at net sample sizes of 1000.
      Citation: Social Science Computer Review
      PubDate: 2022-01-03T11:10:43Z
      DOI: 10.1177/08944393211054939
       
 
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