Subjects -> SOCIAL SCIENCES (Total: 1815 journals)
    - BIRTH CONTROL (22 journals)
    - CHILDREN AND YOUTH (260 journals)
    - FOLKLORE (30 journals)
    - MATRIMONY (16 journals)
    - MEN'S INTERESTS (16 journals)
    - MEN'S STUDIES (96 journals)
    - SEXUALITY (57 journals)
    - SOCIAL SCIENCES (1091 journals)
    - WOMEN'S INTERESTS (44 journals)
    - WOMEN'S STUDIES (183 journals)

SOCIAL SCIENCES (1091 journals)            First | 1 2 3 4 5 6     

Showing 401 - 136 of 136 Journals sorted alphabetically
Identities: Global Studies in Culture and Power     Hybrid Journal   (Followers: 20)
IDS Bulletin     Open Access   (Followers: 17)
IEEE Transactions on Computational Social Systems     Full-text available via subscription   (Followers: 2)
Illness, Crisis & Loss     Full-text available via subscription   (Followers: 3)
Im@go. A Journal of the Social Imaginary     Open Access   (Followers: 1)
imagonautas : Revista interdisciplinaria sobre imaginarios sociales     Open Access  
Immigrants & Minorities     Hybrid Journal   (Followers: 8)
Impact     Full-text available via subscription   (Followers: 2)
In Situ : Au regard des sciences sociales     Open Access   (Followers: 2)
Inclusión y Desarrollo     Open Access  
Indiana University Journal of Undergraduate Research     Open Access  
Indonesia Prime     Open Access   (Followers: 1)
Infinitum: Revista Multidisciplinar     Open Access   (Followers: 1)
Informação em Pauta     Open Access   (Followers: 1)
Informes Científicos - Técnicos UNPA     Open Access  
Infrastructure Complexity     Open Access   (Followers: 6)
Inkanyiso : Journal of Humanities and Social Sciences     Open Access   (Followers: 1)
InPsych : The Bulletin of the Australian Psychological Society Ltd     Full-text available via subscription   (Followers: 2)
INSANCITA : Journal of Islamic Studies in Indonesia and Southeast Asia     Open Access  
Integrated Social Science Journal : Faculty of Social Sciences and Humanities, Mahidol University     Open Access  
Inter Faculty     Open Access  
Interações : Cultura e Comunidade     Open Access  
Interim : Interdisciplinary Journal     Open Access   (Followers: 4)
International and Multidisciplinary Journal of Social Sciences     Open Access   (Followers: 2)
International Communication of Chinese Culture     Hybrid Journal   (Followers: 7)
International Development Planning Review     Hybrid Journal   (Followers: 15)
International E-journal of Advances in Social Sciences (IJASOS)     Open Access  
International Journal for Transformative Research     Open Access   (Followers: 1)
International Journal of Academic Research in Business, Arts & Science     Open Access   (Followers: 2)
International Journal of Applied Behavioral Sciences     Open Access   (Followers: 1)
International Journal of Arab Culture, Management and Sustainable Development     Hybrid Journal   (Followers: 7)
International Journal of Bahamian Studies     Open Access   (Followers: 1)
International Journal of Business and Social Research     Open Access   (Followers: 8)
International Journal of Canadian Studies / Revue internationale d’études canadiennes     Full-text available via subscription   (Followers: 1)
International Journal of Conflict and Violence     Open Access   (Followers: 24)
International Journal of Cultural and Social Studies (IntJCSS)     Open Access   (Followers: 1)
International Journal of Cultural Policy     Hybrid Journal   (Followers: 11)
International Journal of Disaster Risk Reduction     Hybrid Journal   (Followers: 23)
International Journal of Growth and Development     Open Access   (Followers: 1)
International Journal of Humanities and Social Science Research     Open Access  
International Journal of Iberian Studies     Hybrid Journal   (Followers: 6)
International Journal of Information, Diversity, & Inclusion     Open Access  
International Journal of Innovative Research and Scientific Studies     Open Access   (Followers: 5)
International Journal of Innovative Research in Social and Natural Sciences     Open Access   (Followers: 1)
International Journal of Integrated Education and Development     Open Access  
International Journal of Intercultural Relations     Hybrid Journal   (Followers: 14)
International Journal of Knowledge-Based Development     Hybrid Journal   (Followers: 5)
International Journal of Korean Humanities and Social Sciences     Open Access  
International Journal of Language and Culture     Hybrid Journal   (Followers: 4)
International Journal of Management and Social Sciences     Full-text available via subscription   (Followers: 6)
International Journal of Management, Economics and Social Sciences     Open Access   (Followers: 15)
International Journal of Multidisciplinary Studies     Open Access  
International Journal of Punishment and Sentencing, The     Full-text available via subscription   (Followers: 10)
International Journal of Qualitative Methods     Open Access   (Followers: 28)
International Journal of Research in Business and Social Science     Open Access   (Followers: 8)
International Journal of Social and Allied Research     Full-text available via subscription   (Followers: 2)
International Journal of Social and Humanistic Computing     Hybrid Journal   (Followers: 1)
International Journal of Social And Humanities Sciences     Open Access  
International Journal of Social and Organizational Dynamics in IT     Full-text available via subscription   (Followers: 3)
International Journal of Social Research Methodology     Hybrid Journal   (Followers: 75)
International Journal of Social Science Research     Open Access   (Followers: 14)
International Journal of Social Science Studies     Open Access   (Followers: 16)
International Journal of Social Sciences and Education Research     Open Access  
International Journal of Social Sciences and Humanity Studies     Open Access   (Followers: 2)
International Journal of Synergy and Research     Open Access  
International Journal of the Sociology of Leisure     Hybrid Journal  
International Journal of Undergraduate Research and Creative Activities     Open Access   (Followers: 2)
International Journal Pedagogy of Social Studies     Open Access  
International Quarterly for Asian Studies     Open Access   (Followers: 2)
International Review of Qualitative Research     Full-text available via subscription   (Followers: 33)
International Review of Social Research     Open Access   (Followers: 3)
International Scholarly Research Notices     Open Access   (Followers: 232)
International Social Science Journal     Hybrid Journal   (Followers: 24)
International Studies. Interdisciplinary Political and Cultural Journal     Open Access   (Followers: 9)
Internationale Revue Fur Soziale Sicherheit     Hybrid Journal   (Followers: 1)
InterSciencePlace     Open Access   (Followers: 1)
Intersticios Sociales     Open Access   (Followers: 1)
Investigación Valdizana     Open Access  
Investigación y Desarrollo     Open Access   (Followers: 1)
Investigaciones Geográficas (Esp)     Open Access  
Irish Journal of Applied Social Studies     Open Access   (Followers: 5)
Issues in Social Science     Open Access   (Followers: 5)
Ithaca : Viaggio nella Scienza     Open Access  
IULC Working Papers     Open Access  
Ius et Praxis     Open Access  
Iztapalapa : Revista de ciencias sociales y humanidades     Open Access   (Followers: 1)
Izvestia Ural Federal University Journal. Series 3. Social and Political Sciences     Open Access  
J : Multidisciplinary Scientific Journal     Open Access  
Janapriya Journal of Interdisciplinary Studies     Open Access   (Followers: 1)
JICSA : Journal of Islamic Civilization in Southeast Asia     Open Access  
JISIP-UNJA : Jurnal Ilmu Sosial dan Ilmu Politik Fisipol Universitas Jambi     Open Access   (Followers: 1)
Journal for New Generation Sciences     Open Access   (Followers: 4)
Journal for Semitics     Full-text available via subscription   (Followers: 8)
Journal for Undergraduate Ethnography     Open Access   (Followers: 3)
Journal of Addiction & Prevention     Open Access   (Followers: 1)
Journal of Advanced Academic Research     Open Access   (Followers: 3)
Journal of Agriculture and Social Research (JASR)     Open Access   (Followers: 5)
Journal of Agriculture, Forestry and the Social Sciences     Full-text available via subscription   (Followers: 5)
Journal of Applied Social Psychology     Hybrid Journal   (Followers: 58)
Journal of Applied Social Science     Hybrid Journal   (Followers: 17)
Journal of Arabic and Islamic Studies     Open Access   (Followers: 1)
Journal of Arts and Social Sciences     Open Access   (Followers: 1)
Journal of ASIAN Behavioural Studies     Open Access   (Followers: 4)
Journal of Burirum Rajabhat University     Open Access  
Journal of Business and Social Sciences     Open Access  
Journal of Business and Social Sciences Research     Open Access  
Journal of Cape Verdean Studies     Open Access   (Followers: 3)
Journal of Cognition and Culture     Hybrid Journal   (Followers: 19)
Journal of Community Development and Life Quality     Open Access  
Journal of Community Services and Engagement     Open Access   (Followers: 5)
Journal of Comparative Family Studies     Full-text available via subscription   (Followers: 3)
Journal of Comparative Social Welfare     Hybrid Journal   (Followers: 18)
Journal of Computational Social Science     Hybrid Journal  
Journal of Contemporary African Studies     Hybrid Journal   (Followers: 4)
Journal of Critical Race inquiry     Open Access   (Followers: 10)
Journal of Cultural Economy     Hybrid Journal   (Followers: 10)
Journal of Cultural Heritage     Full-text available via subscription   (Followers: 17)
Journal of Development Effectiveness     Hybrid Journal   (Followers: 7)
Journal of Economy Culture and Society     Open Access  
Journal of Educational Social Studies     Open Access   (Followers: 9)
Journal of Family & Consumer Sciences     Full-text available via subscription   (Followers: 1)
Journal of Family Studies     Hybrid Journal   (Followers: 22)
Journal of Geography, Politics and Society     Open Access  
Journal of Globalization and Development     Hybrid Journal   (Followers: 13)
Journal of Graduate Research     Open Access  
Journal of Graduate School Sakon Nakhon Rajabhat University     Open Access  
Journal of Graduate Studies in Northern Rajabhat Universities     Open Access  
Journal of Graduate Studies Valaya Alongkorn Rajabhat University     Open Access  
Journal of Human Security     Open Access   (Followers: 10)
Journal of Humanities and Social Sciences     Open Access   (Followers: 1)
Journal of Humanities and Social Sciences Surin Rajabhat University     Open Access  
Journal of Humanities and Social Sciences, Rajapruk University     Open Access  
Journal of Ilahiyat Researches     Open Access  
Journal of Indian Ocean World Studies     Open Access   (Followers: 2)
Journal of Interdisciplinary Gender Studies: JIGS     Full-text available via subscription   (Followers: 17)
Journal of International and Comparative Social Policy     Hybrid Journal   (Followers: 2)
Journal of International Social Studies     Open Access   (Followers: 1)
Journal of Korean Studies     Full-text available via subscription   (Followers: 12)
Journal of Language and Social Psychology     Hybrid Journal   (Followers: 13)
Journal of Markets & Morality     Partially Free  
Journal of Mediterranean Knowledge     Open Access   (Followers: 7)
Journal of Men, Masculinities and Spirituality     Full-text available via subscription   (Followers: 13)
Journal of Methods and Measurement in the Social Sciences     Open Access   (Followers: 4)
Journal of Migration and Refugee Issues, The     Full-text available via subscription   (Followers: 34)
Journal of Multicultural Affairs     Open Access   (Followers: 1)
Journal of New Brunswick Studies / Revue d’études sur le Nouveau-Brunswick     Open Access   (Followers: 4)
Journal of Organisational Transformation & Social Change     Hybrid Journal   (Followers: 8)
Journal of Pan African Studies     Open Access   (Followers: 2)
Journal of Personality and Social Psychology     Full-text available via subscription   (Followers: 364, SJR: 4.302, CiteScore: 6)
Journal of Policy Practice     Hybrid Journal   (Followers: 5)
Journal of Policy Practice and Research     Hybrid Journal   (Followers: 3)
Journal of Population and Sustainability     Open Access   (Followers: 1)
Journal of Poverty and Social Justice     Hybrid Journal   (Followers: 31)
Journal of Progressive Research in Social Sciences     Open Access   (Followers: 5)
Journal of Purdue Undergraduate Research     Open Access   (Followers: 1)
Journal of Relationships Research     Hybrid Journal   (Followers: 5)
Journal of Religion & Spirituality in Social Work: Social Thought     Hybrid Journal   (Followers: 12)
Journal of Research in National Development     Full-text available via subscription  
Journal of Responsible Innovation     Hybrid Journal   (Followers: 7)
Journal of Social Change     Open Access   (Followers: 8)
Journal of Social Development in Africa     Full-text available via subscription   (Followers: 8)
Journal of Social Distress and the Homeless     Hybrid Journal   (Followers: 6)
Journal of Social Intervention: Theory and Practice     Open Access   (Followers: 3)
Journal of Social Issues     Hybrid Journal   (Followers: 19)
Journal of Social Philosophy     Hybrid Journal   (Followers: 26)
Journal of Social Science Education : JSSE     Open Access  
Journal of Social Science Studies     Open Access   (Followers: 13)
Journal of Social Sciences     Open Access   (Followers: 16)
Journal of Social Sciences and Humanities Review     Open Access  
Journal of Social Structure     Open Access   (Followers: 1)
Journal of Social Studies Research     Full-text available via subscription   (Followers: 16)
Journal of Studies in Social Sciences     Open Access   (Followers: 6)
Journal of Technology in Human Services     Hybrid Journal   (Followers: 4)
Journal of the Bangladesh Association of Young Researchers     Open Access   (Followers: 1)
Journal of the Polynesian Society     Full-text available via subscription   (Followers: 7)
Journal of the Society for Social Work and Research     Full-text available via subscription   (Followers: 14)
Journal of the University of Ruhuna     Open Access   (Followers: 1)
Journal of Transnational American Studies     Open Access   (Followers: 3)
Journal of Trust Management     Open Access   (Followers: 4)
Journal Sampurasun : Interdisciplinary Studies for Cultural Heritage     Open Access   (Followers: 1)
Jurnal Abdimas     Open Access  
Jurnal Biometrika dan Kependudukan     Open Access   (Followers: 1)
Jurnal Ilmiah Ilmu Sosial     Open Access   (Followers: 1)
Jurnal Ilmiah Peuradeun     Open Access   (Followers: 3)
Jurnal Ilmu Sosial dan Humaniora     Open Access  
Jurnal Karya Abdi Masyarakat     Open Access   (Followers: 1)
Jurnal Kawistara     Open Access  
Jurnal Lakon     Open Access  
Jurnal Masyarakat dan Budaya     Open Access  
Jurnal Pendidikan Ilmu Sosial     Open Access   (Followers: 1)
Jurnal Sosial Humaniora     Open Access   (Followers: 2)
Jurnal Teori dan Praksis Pembelajaran IPS     Open Access  
Jurnal Terapan Abdimas     Open Access  
Just Policy: A Journal of Australian Social Policy     Full-text available via subscription   (Followers: 18)
Kaleidoscope     Open Access  
Kasetsart Journal of Social Sciences     Open Access   (Followers: 2)
Kervan. International Journal of Afro-Asiatic Studies     Open Access  
Kimün. Revista Interdisciplinaria de Formación Docente     Open Access  
Kırklareli Üniversitesi Sosyal Bilimler Dergisi     Open Access  
KnE Social Sciences     Open Access   (Followers: 1)

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Similar Journals
Journal Cover
IEEE Transactions on Computational Social Systems
Journal Prestige (SJR): 0.428
Citation Impact (citeScore): 2
Number of Followers: 2  
  Full-text available via subscription Subscription journal
ISSN (Online) 2329-924X
Published by IEEE Homepage  [229 journals]
  • IEEE publication information
    • Abstract: Provides a listing of current staff, committee members and society officers.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • IEEE Transactions on Computational Social Systems society information
    • Abstract: Provides a listing of current committee members and society officers.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • IEEE Transactions on Computational Social Systems information for authors
    • Abstract: Provides instructions and guidelines to prospective authors who wish to submit manuscripts.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Parallel Blockchain: An Architecture for CPSS-Based Smart Societies
    • Authors: Fei-Yue Wang;Yong Yuan;Chunming Rong;Jun Jason Zhang;
      Pages: 303 - 310
      Abstract: Time flies fast, it has been already one year since I was appointed as the Editor-in-Chief of this great publication, and thanks to the strong support and dedication of our associate editors, editorial staff, anonymous reviewers, and authors, we have made solid progress and I really enjoy my work and our achievement so far. At this point, significant improvements in the timeliness and quality of the review process, as well as the numbers of manuscripts submitted and articles published have been accomplished.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Representation and Matching of Team Managers: An Experimental Research
    • Authors: Cong Yang;Olaf Flak;Marcin Grzegorzek;
      Pages: 311 - 323
      Abstract: The main goal of this paper is to provide an effective approach to quantify patterns of team managers so that they can be learned and compared by machines. Traditionally, team managers are analyzed and compared based on the data collected from surveys and questionnaires. Then, managers are usually represented by managerial roles/skills and analyzed semimanually by human perception. However, it causes two methodological problems: 1) managerial roles and skills are usually isolated and only indirectly related to managerial actions and 2) the perception-based methods cannot provide detailed analysis results since human perception is abstract and lacks stability. In order to solve these problems, we propose a simple but powerful manager representation method which is general enough to cover most manager types. With this, team managers can be learned and compared my machines. Particularly, we represent a manager by managerial actions with flexible feature groups to improve the expandability and description power of the proposed representation model. For manager analysis, we introduce the first matching algorithm which not only returns robust and stable manager similarities but also details the matched parts among managerial action sequences. The efficiency of the proposed methods is substantiated by comparison experiments between machines and human perception.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Truthful Incentive Mechanisms for Geographical Position Conflicting Mobile
           Crowdsensing Systems
    • Authors: Ji Li;Zhipeng Cai;Jinbao Wang;Meng Han;Yingshu Li;
      Pages: 324 - 334
      Abstract: Sensor-embedded smartphones have become ubiquitous nowadays, further leveraging the popularity of mobile crowdsensing. A mobile crowdsensing platform gathers sensory data from smartphone users and makes payments to them in return. Due to the spatial correlation of sensory data in various applications, users close to each other in geographical positions usually provide similar sensory data, and it is quite an economic waste for a mobile sensing platform to buy duplicated sensory data with multiple payments to geographically close users. Unfortunately, the existing works do not take this matter into consideration. To prevent waste, our paper considers geographical position conflicting mobile crowdsensing systems in which any two users within a limited geographical distance cannot obtain payments simultaneously while participating in crowdsensing tasks. Two algorithms are proposed to select appropriate mobile crowdsensing participants and calculate the payments to them. Solid theoretical proofs are presented to demonstrate the beneficial properties of our proposed algorithms. The extensive experiment results based on real-world datasets indicate that our proposed algorithms are efficient while providing beneficial properties.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Who Spread That Rumor: Finding the Source of Information in Large Online
           Social Networks With Probabilistically Varying Internode Relationship
    • Authors: Alireza Louni;K. P. Subbalakshmi;
      Pages: 335 - 343
      Abstract: We address the problem of estimating the source of a rumor in large-scale social networks. Previous works studying this problem have mainly focused on graph models with deterministic and homogenous internode relationship strengths. However, internode relationship strengths in real social networks are random. We model this uncertainty by using random, nonhomogenous edge weights on the underlying social network graph. We propose a novel two-stage algorithm that uses the modularity of the social network to locate the source of the rumor with fewer sensor nodes than other existing algorithms. We also propose a novel method to select these sensor nodes. We evaluate our algorithm using a large data set from Twitter and Sina Weibo. Real-world time series data are used to model the uncertainty in social relationship strengths. Simulations show that the proposed algorithm can determine the actual source within two hops, 69%–80% of the time, when the diameter of the networks varies between 7 and 13. Our numerical results also show that it is easier to estimate the source of a rumor when the source has higher betweenness centrality. Finally, we demonstrate that our two-stage algorithm outperforms the alternative algorithm in terms of the accuracy of localizing the source.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Boosting Information Spread: An Algorithmic Approach
    • Authors: Yishi Lin;Wei Chen;John C. S. Lui;
      Pages: 344 - 357
      Abstract: The majority of influence maximization (IM) studies focus on targeting influential seeders to trigger substantial information spread in social networks. Motivated by the observation that incentives could “boost” users so that they are more likely to be influenced by friends, we consider a new and complementary $k$ -boosting problem which aims at finding $k$ users to boost so as to trigger a maximized “boosted” influence spread. The $k$ -boosting problem is different from the IM problem, because boosted users behave differently from seeders. Boosted users are initially uninfluenced, and we only increase their probability to be influenced. This paper also complements the IM studies, because we focus on triggering a larger influence spread on the basis of given seeders. Both the NP-hardness of the problem and the nonsubmodularity of the objective function pose challenges to the $k$ -boosting problem. To tackle the problem on general graphs, we devise two efficient algorithms with the data-dependent approximation ratio. To tackle the problem on bidirected trees, we present an efficient greedy algorithm and a dynamic programming that is a fully polynomial-time approximation scheme. Experiments using real social networks and synthetic bidirected trees verify the efficiency and effectiveness of the proposed algorithms. In particular, on general graphs, boosting solutions returned by our algorithms achieves boosts of influence that are up to several times higher than those achieved by boosting intuitive solutions w-th no approximation guarantee. We also explore the “budget allocation” problem experimentally, demonstrating the benefits of allocating the budget to both seeders and boosted users.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • FlexCCT: A Methodological Framework and Software for Ratings Analysis and
           Wisdom of the Crowd Applications
    • Authors: Stephen L. France;Mahyar Sharif Vaghefi;William H. Batchelder;
      Pages: 358 - 370
      Abstract: Flexible cultural consensus theory (FlexCCT) provides an integrated framework and tool set for analyzing and aggregating ratings. It utilizes a likelihood-based statistical model to create aggregate ratings weighted for rater competencies and rater biases. It has features for the analysis of multiple rating cultures and for consensus adjusted reliability. Multiple optimization algorithms are implemented for FlexCCT, along with a range of model identifiability options to restrict certain subsets of the model parameters. Bootstrapping- and jackknifing-based methods are implemented to give confidence intervals for parameters. A holdout validation method that generates a measure of “prediction log-likelihood” allows for the testing of solution reliability and stability. Empirical work demonstrates the utility of FlexCCT on unsupervised wisdom of the crowd problems, and an example shows how FlexCCT can be used to analyze educational grading data.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Extracting Social Network and Character Categorization From Bengali
    • Authors: Samya Muhuri;Susanta Chakraborty;Sabitri Nanda Chakraborty;
      Pages: 371 - 381
      Abstract: Literature network analysis is an emerging area in the computational research domain. Literature network is a type of social network with various distinct features. The analysis explores significance of human behavior and complex social relationships. The story consists of some characters and creates an interconnected social system. Each character of the literature represents a node and the edge between any two nodes offered the interaction between them. An annotation and a novel character categorization method are developed to extract interactive social network from the Bengali drama. We analyze Raktakarabi and Muktodhara, two renowned Bengali dramas of Rabindranath Tagore. Weighted degree, closeness, and betweenness centrality analyze the correlation among the characters. We propose an edge contribution-based centrality and diversity metric of a node to determine the influence of one character over others. High diverse nodes show low clustering coefficient and vice versa. We propose a novel idea to analyze the characteristics of protagonist and antagonist from the influential nodes based on the complex graph. We also present a game theory-based community detection method that clusters the actors with a high degree of relationship. Evaluation on real-world networks demonstrates the superiority of the proposed method over the other existing algorithms. Interrelationship of the actors within the drama is also shown from the detected communities, as underlying theme of the narrations is identical. The analytical results show that our method efficiently finds the protagonist and antagonist from the literature network. The method is unique, and the analytical results are more accurate and unbiased than the human perspective. Our approach establishes similar results compared with the benchmark analysis available in Tagore’s Bengali literature.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Modeling Market Share Dynamics Under Advertising Effort and Word-of-Mouth
           Interactions Between Customers
    • Authors: Eugenius Kaszkurewicz;Amit Bhaya;
      Pages: 382 - 390
      Abstract: This paper presents a complete analysis of a new model of market share dynamics under advertising effort, taking into account word-of-mouth (WOM) interactions between satisfied customers, dissatisfied defectors, as well as undecided customers. The populations of satisfied customers and defectors are both modeled as competing predators preying on a population of undecided customers, using Lotka–Volterra-type interaction terms, which have also been used in a related, but different, class of WOM and electronic WOM models. The proposed model describes the dynamics of market share from arbitrary nonnegative initial conditions, up to and including the market in which there are no longer any undecided customers, thereby extending both the classical Vidale–Wolfe model in which the market with no undecided customers is never reached at equilibrium due to the positive decay term, as well as the Lanchester model which only deals with the market with no undecided customers. Another new feature of the proposed model is that, even under constant advertising effort, and fixed values of interaction coefficients, different outcomes can arise, depending on the initial fractions of satisfied customers and defectors. The design of a class of advertising policies that attain a desired market share is also presented, with corresponding numerical simulations.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Corporate Communication Network and Stock Price Movements: Insights From
           Data Mining
    • Authors: Pei-Yuan Zhou;Keith C. C. Chan;Carol Xiaojuan Ou;
      Pages: 391 - 402
      Abstract: Grounded on communication theories, we propose to use a data-mining algorithm to detect communication patterns within a company to determine if such patterns may reveal the performance of the company. Specifically, we would like to find out whether or not there exist any association relationships between the frequency of e-mail exchange of the key employees in a company and the performance of the company as reflected in its stock prices. If such relationships do exist, we would also like to know whether or not the company’s stock price could be accurately predicted based on the detected relationships. To detect the association relationships, a data-mining algorithm is proposed here to mine e-mail communication records and historical stock prices so that based on the detected relationship, rules that can predict changes in stock prices can be constructed. Using the data-mining algorithm and a set of publicly available Enron e-mail corpus and Enron’s stock prices recorded during the same period, we discovered the existence of interesting, statistically significant, association relationships in the data. In addition, we also discovered that these relationships can predict stock price movements with an average accuracy of around 80%. The results confirm the belief that corporate communication has identifiable patterns and such patterns can reveal meaningful information of corporate performance as reflected by such indicators as stock market performance. Given the increasing popularity of social networks, the mining of interesting communication patterns could provide insights into the development of many useful applications in many areas.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Characterizing and Countering Communal Microblogs During Disaster Events
    • Authors: Koustav Rudra;Ashish Sharma;Niloy Ganguly;Saptarshi Ghosh;
      Pages: 403 - 417
      Abstract: The huge amount of tweets posted during a disaster event includes information about the present situation as well as the emotions/opinions of the masses. While looking through these tweets, we realized that a large amount of communal tweets, i.e., abusive posts targeting specific religious/racial groups are posted even during natural disasters—this paper focuses on such category of tweets, which is in sharp contrast to most of the prior research concentrating on extracting situational information. Considering the potentially adverse effects of communal tweets during disasters, in this paper, we develop a classifier to distinguish communal tweets from noncommunal ones, which performs significantly better than existing approaches. We also characterize the communal tweets posted during five recent disaster events, and the users who posted such tweets. Interestingly, we find that a large proportion of communal tweets are posted by popular users (having tens of thousands of followers), most of whom are related to media and politics. Further, users posting communal tweets form strong connected groups in the social network. As a result, the reach of communal tweets is much higher than noncommunal tweets. We also propose an event-independent classifier to automatically identify anticommunal tweets and also indicate a way to counter communal tweets, by utilizing such anticommunal tweets posted by some users during disaster events. Finally, we develop a real-time service to automatically collect tweets related to a disaster event and identify communal and anticommunal tweets from that set. We believe that such a system is really helpful for government and local monitoring agencies to take appropriate decisions like filtering or promoting some particular contents.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Multiplex Influence Maximization in Online Social Networks With
           Heterogeneous Diffusion Models
    • Authors: Alan Kuhnle;Md Abdul Alim;Xiang Li;Huiling Zhang;My T. Thai;
      Pages: 418 - 429
      Abstract: Motivated by online social networks that are linked together through overlapping users, we study the influence maximization problem on a multiplex, with each layer endowed with its own model of influence diffusion. This problem is a novel version of the influence maximization problem that necessitates new analysis incorporating the type of propagation on each layer of the multiplex. We identify a new property, generalized deterministic submodular, which when satisfied by the propagation in each layer, ensures that the propagation on the multiplex overall is submodular–for this case, we formulate influential seed finder (ISF), the greedy algorithm with approximation ratio $(1-1/e)$ . Since the size of a multiplex comprising multiple OSNs may encompass billions of users, we formulate an algorithm knapsack seeding of network (KSN) that runs on each layer of the multiplex in parallel. KSN takes an $alpha $ -approximation algorithm $A$ for the influence maximization problem on a single network as input, and has approximation ratio $({(1 - epsilon) alpha })/({(o + 1)k})$ for arbitrary $epsilon > 0$ , $o$ is the number of overlapping users, and $k$ is the number of layers in the multiplex. Experiments on real and synthesized multiplexes validate the efficacy of the proposed algorithms for the problem of influence maximization in the heterogeneous multiplex. Implementations of ISF and KSN are available at http://www.alankuhnle.c-m/papers/mim/mim.html.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • 3-HBP: A Three-Level Hidden Bayesian Link Prediction Model in Social
    • Authors: Yunpeng Xiao;Xixi Li;Haohan Wang;Ming Xu;Yanbing Liu;
      Pages: 430 - 443
      Abstract: In social networks, link establishment among the users is affected by complex factors. In this paper, we try to investigate the internal and external factors that affect the formation of links and propose a three-level hidden Bayesian link prediction model by integrating the user behavior as well as user relationships to link prediction. First, based on the user multiple interest characteristics, a latent Dirichlet allocation (LDA) traditional text modeling method is applied into user behavior modeling. Taking the advantage of LDA topic model in dealing with the problem of polysemy and synonym, we can mine user latent interest distribution and analyze the effects of internal driving factors. Second, owing to the power-law characteristics of user behavior, LDA is improved by Gaussian weighting. In this way, the negative impact of the interest distribution to the high-frequency users can be reduced and the expression ability of interests can be enhanced. Furthermore, taking the impact of common neighbor dependencies in link establishment, the model can be extended with hidden naive Bayesian algorithm. By quantifying the dependencies between common neighbors, we can analyze the effects of external driving factors and combine internal driving factors to link prediction. Experimental results indicate that the model can not only mine user latent interest distribution but also can improve the performance of link prediction effectively.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Modeling Human Behavior on Social Media in Response to Significant Events
    • Authors: Yulia Tyshchuk;William A. Wallace;
      Pages: 444 - 457
      Abstract: Social media provides abundant, naturally occurring data on communications among people that can reveal their behavior. Recent technological advancements have made possible the rapid processing of social media data with the potential to learn more about human behavior. In order to do so, however, there is a need for a comprehensive and integrative theoretical model of human behavior as expressed in social media. In addition, such a model should provide specific avenues for staging behavioral interventions. The objective of this paper is to address this deficiency in the context of behaviors that occur in response to significant events. Relevant theories of human behavior are presented as well as a methodology, utilizing natural language processing and social network analysis, for measuring elements of human behavior. The methodology provides numerical measures for each element, which serve as input data for the multivariate statistical model used to answer research questions in a case study of human behavior in response to a natural disaster. For this case study, three behaviors associated with the warning response process were modeled: 1) obtain and propagate the warning; 2) seek additional information/confirmation; and 3) take the prescribed action. Emergency managers can use the findings of the research to help ensure that people obtain critical information and take prescribed actions, such as evacuating a flood zone. Once the dynamics of human behavior as expressed in social media are understood, models can be built to predict human behaviors well in advance of their recommended or anticipated occurrence.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • A Socio-Computational Approach to Predicting Bioweapon Proliferation
    • Authors: Ghita Mezzour;William Frankenstein;Kathleen M. Carley;Larry Richard Carley;
      Pages: 458 - 467
      Abstract: Predicting countries that will seek bioweapons (BW) enables the international community to act early in order to prevent these countries from acquiring such weapons. Unfortunately, the literature on countries’ BW programs mainly consists of case studies that focus on one or a few countries. Although case studies are valuable, they are typically not predictive. Moreover, case studies require substantial effort and expertise, and are thus unfeasible for all countries. In this paper, we develop a computational methodology that predicts countries that will seek BW. Our methodology consists of a sociocultural model and indicators that computationally capture expert opinions about why and how countries acquire BW. Our methodology systematically examines all countries in the world and can be used by non-BW experts based on publicly available data. We validate our methodology by examining the methodology’s ability to predict historical BW proliferators.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Distributed Rumor Blocking With Multiple Positive Cascades
    • Authors: Guangmo Tong;Weili Wu;Ding-Zhu Du;
      Pages: 468 - 480
      Abstract: Misinformation and rumor can spread rapidly and widely through online social networks and therefore rumor controlling has become a critical issue. It is assumed in the existing works that there is a single authority whose goal is to minimize the spread of rumor by generating a positive cascade. In this paper, we study a more realistic scenario when there is multiple positive cascades generated by different agents. For the multiple-cascade diffusion, we propose the peer-to-peer independent cascade model for private social communications. The main contribution of this paper is an analysis of the rumor blocking effect (i.e., the number of the users activated by rumor) when the agents noncooperatively generate the positive cascades. We show that the rumor blocking effect provided by the Nash equilibrium will not be arbitrarily worse even if the positive cascades are generated noncooperatively. In addition, we give a discussion on how the cascade priority and activation order affect the rumor blocking problem. We experimentally examine the Nash equilibrium of the proposed games by simulations done on real social network structures.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • A Distributed HOSVD Method With Its Incremental Computation for Big Data
           in Cyber-Physical-Social Systems
    • Authors: Xiaokang Wang;Wei Wang;Laurence T. Yang;Siwei Liao;Dexiang Yin;M. Jamal Deen;
      Pages: 481 - 492
      Abstract: Cyber-physical-social systems (CPSS), integrating cyber, physical, and social spaces together, bring both conveniences and challenges to humans. For practical applications and user convenience, it is essential that the Big Data produced in CPSS be processed in real time. Therefore, Big Data computation should avoid redundant computations on historical data when dealing with periodic incoming data. In this paper, we propose a columnwise high-order singular value decomposition (HOSVD) algorithm to realize dimensionality reduction, extraction, and noise reduction for tensor-represented Big Data. First, the distributed HOSVD (DHOSVD) is proposed using the columnwise Jacobi-based approach to realize the distributed computation of HOSVD. Second, big streaming data are continuously produced and the intermediate results could be recorded for the next computational step. Third, we propose a similar columnwise incremental HOSVD (IHOSVD) scheme to support online computation on temporally incremental data streaming. The performance of the two HOSVD-based schemes will illustrate the scalability of our efficient real-time Big Data processing methods.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Disjoint Community Detection in Networks Based on the Relative Association
           of Members
    • Authors: Kamal Taha;
      Pages: 493 - 507
      Abstract: We propose in this paper a hybrid system called DCD_RAM that detects disjoint communities. It is based, in part, on the underlying techniques of the network-centric, hierarchycentric, vertex-centric, and group-centric approaches. It adopts most of the underlying techniques of the four approaches. Most of these approaches work well in only networks with certain topologies. DCD_RAM aims at overcoming the limitations of each of the four approaches to enable it to work well in networks with all types of topologies. It does so by: 1) measuring the betweenness of each edge (u, v) in such a way that the betweenness acts as an indicator of the influences of vertices u and v over the flow of information in the entire network; 2) employing a novel logarithm-based formula that captures and further enhances the eigenvector principle in order to characterize the global influence of each vertex in the network; 3) employing a novel agglomerative-like formula that discovers natural divisions of a network; and 4) employing a novel belonging formula that helps in discovering disjoint communities. We evaluated DCD_RAM by comparing it empirically and experimentally with nine methods. Results showed marked improvement.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Modern Food Foraging Patterns: Geography and Cuisine Choices of Restaurant
           Patrons on Yelp
    • Authors: Qi Xuan;Mingming Zhou;Zhi-Yuan Zhang;Chenbo Fu;Yun Xiang;Zhefu Wu;Vladimir Filkov;
      Pages: 508 - 517
      Abstract: Animals search for food based on certain optimal principles and over time form foraging patterns effective for survival in changing environments. Due to the many choices available in modern society, we also face a decision on where to get their food. We call this “modern human food foraging,” since the Internet makes foraging much more convenient than before. People search online for food venues, or restaurants, through websites such as Yelp, and write reviews for the food they tasted, which in turn, facilitate others’ searches in the future. These activities make the whole community of restaurant patrons wiser over time. Moreover, the archives of all these choices and evaluations are publicly available, and can help researchers better understand human foraging patterns in modern society. In this paper, we use a Yelp data set to study modern human food foraging patterns, with respect to both geography and cuisine. To understand spatial patterns, we cluster reviewed restaurants geographically and construct a taste similarity network, representing the topology of restaurant cuisine space. We find that people steadily expand their foraging domains from the nearest to them to the distant in geography and from the most familiar to the novel in cuisine. Using longitudinal data of restaurant reviews, we build a geographical foraging network and a taste foraging network for each patron based on which, we propose three kinds of entropies to characterize foraging patterns. We show that the modern foraging patterns of restaurant patrons in both geography and cuisine are of high regularity, indicating that their behaviors are rather predictable. The foraging patterns are also associated with individual social status in the community. Namely, people having a higher variety in the restaurant cuisines they have visited, but fewer actual locations they visited, tend to attract more followers.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Dynamics of Uncertain and Conflicting Opinions in Social Networks
    • Authors: Jin-Hee Cho;
      Pages: 518 - 531
      Abstract: In this paper, we study the evolution of opinions where people are not sure of their own opinions and/or their opinions may be conflicting to others’ in social networks. We model two types of agents so-called informed agents (IAs) and uninformed agents (UIAs). The IAs have a strong opinion agreeing or disagreeing toward a proposition without being influenced by other agents’ opinions and have a high confidence (low uncertainty) toward its own opinion. The UIAs have a weak opinion without either agreeing or disagreeing toward a proposition and lack confidence with a high uncertainty. Based on subjective logic, we consider a binomial opinion to deal with an opinion with a degree of uncertainty. We develop two types of trust attitudes for agents to update their opinions upon their interactions with other agents: uncertainty-based trust (UT) and similarity-based trust (ST). In the UT, a UIA updates its opinion based on an interacting agent’s uncertainty toward a proposition. In the ST, a UIA updates its opinion based on the degree of similarity between its own opinion and the interacting agent’s opinion toward the proposition. Our results show that more IAs slow down the convergence of the opinions under the UT while they can quickly lead to opinion convergence under the ST. In addition, the ST leads uncertain opinions to two extremes, either 0 or 1, if consensus exists. On the other hand, the UT can make opinions converge to a certain point between two extreme opinions although the converged point is significantly affected by the dominant agents’ opinions. Furthermore, we observe that under the UT, more IAs with a high centrality increase dissonance of opinions, while more IAs with a low centrality offer better chances for opinion consensus in both the UT and the ST.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Nature-Inspired Computational Model of Population Desegregation Under
           Group Leaders Influence
    • Authors: Kashif Zia;Dinesh Kumar Saini;Arshad Muhammad;Alois Ferscha;
      Pages: 532 - 543
      Abstract: This paper presents an agent-based model of population desegregation and provides a thorough analysis of the social behavior leading to it, namely, the contact hypothesis. Based on the parameters of frequency and intensity of influence of group leaders on the population, the proposed model is constituted by two layers: 1) a physical layer of the population that is influenced by and 2) a virtual layer of group leaders. The model of negotiation and survival of group leaders are governed by the nature-inspired evolutionary process of queen ants, also known as Foundress Dilemma. The motivation of using a virtual grouping concept (instead of taking a subset of population as the group leaders) is to stay focused on finding the conditions leading individuals in a society tolerating a significantly diversified (desegregated) neighborhood, rather than, indulging into complex details, which would be more relevant to studies targeting the evolution of societal group and leaders. A geographic information system-driven simulation is performed, which reveals that: 1) desegregation is directly proportional to the frequency of group leaders’ contact with the population and 2) mostly, it remains ineffective with an increase in the intensity of group leaders’ contact with the population. The mechanism of group selection (the conflict resolution model resolving the Foundress Dilemma) reveals an exciting result concerning negative influence of cooperative group leaders. Most of the time, desegregation decreases with increase in cooperative leaders (the leaders enforcing desegregation) when compared with fierce leaders (the leaders enforcing segregation).
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • A Quantitative Study of Factors Influence on Evacuation in Building Fire
    • Authors: Yuling Hu;Xiao Wang;Fei-Yue Wang;
      Pages: 544 - 552
      Abstract: In order to decrease the casualties in fire disasters and to improve the efficiency of evacuation, exploring, and revealing the impact of influence factors on evacuation is of vital importance. This paper is focused on the influence of fire and human factors on evacuation processes directed by evacuation strategies in the building structure. Interactions between fire environment and evacuees are considered in a systematic view. Building artificial evacuation systems and performing computational experiments are the main research ways. A case is given to illustrate the research approach and quantitative results have been analyzed. The work in this paper can be used for optimizing occupant distribution and composition, estimating evacuation strategies, and ultimately for improving the evacuation efficiency.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • PMP-Based Set-Point Optimization and Sliding-Mode Control of Vehicular
    • Authors: Ge Guo;Dandan Li;
      Pages: 553 - 562
      Abstract: This paper investigates the problem of set-point optimization and speed tracking control for fuel–time-efficient platooning of vehicles on freeways. A two-layered control architecture is presented for vehicular platooning systems: a set-point optimization layer and a vehicle tracking control layer. In the first layer, a speed-planning algorithm is derived to calculate the speed set-point for the platoon by averaging the optimal speed of each vehicle, which is obtained by solving a fuel–time optimization problem based on Pontryagin’s minimum principle. The second layer contains a set of distributed sliding-mode controllers for vehicle tracking control, which can guarantee string stability of the vehicular platoon with a desired intervehicle spacing. The effectiveness of the presented method is demonstrated via simulations.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • Influence Propagation Model for Clique-Based Community Detection in Social
    • Authors: Noha Alduaiji;Amitava Datta;Jianxin Li;
      Pages: 563 - 575
      Abstract: Social media community detection is a fundamental challenge in social data analytics, in order to understand user relationships and improve social recommendations. Although the problem has been extensively investigated, the majority of research has been based on social networks with static structures. Our findings within large social networks, such as Twitter, show that only a few users have interactions or communications at fixed time intervals. Finding active communities that demonstrate constant interactions between its members comprises a reasonable perspective. Communities examined from this perspective will provide time-variant social relationships, which may greatly improve the applicability of social data analytics. In this paper, we address the problem of temporal interaction-biased community detection using a four-step process. First, we develop a partition approach using an objective function based on clique structure, to enhance the time efficiency of our methodology. Second, we develop an influence propagation model that gives greatest weight to active edges or to inactive edges in close proximity to active edges. Third, we develop expansion-driven algorithms to efficiently find the activity-biased densest community. Finally, we verify the effectiveness of the extended community metric and the efficiency of the algorithms using three real data sets and a case study conducted on Twitter dynamic data set.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • An Analysis of Taxi Driver’s Route Choice Behavior Using the Trace
    • Authors: Li Li;Shuofeng Wang;Fei-Yue Wang;
      Pages: 576 - 582
      Abstract: Understanding travelers’ route choice behavior is a key task in transportation studies. In this paper, we analyze the route choices of Beijing taxi drivers regarding four frequently mentioned cost-based route choice rules: pursuing shortest time, or distance, avoiding passing signalized intersections, or making left/right turnings. Test results show that route choices of drivers are not always optimal according to either of these rules. Instead, we argue that taxi drivers are bounded rational and usually choose a satisfactory route that belongs to one of the few routes that consume the shortest times. Test results show that more than 90% observed traces can be explained by this simple explanation.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
  • The Reserve Price of Ad Impressions in Multi-Channel Real-Time Bidding
    • Authors: Juanjuan Li;Xiaochun Ni;Yong Yuan;
      Pages: 583 - 592
      Abstract: With the application of big data analytics in online marketing, real-time bidding (RTB) has developed to be the primary business model and also the major online advertising channel. Due to the precise analysis of Web Cookies, RTB platforms can target the visiting audiences and then forward their generated ad impressions to demanding advertisers who bid on the best-matched audience in a real-time fashion. In RTB markets, the reserve price plays the vital role as a tuner to exclude over-low bids, and hence guarantee the desirable sales prices and revenues for publishers from ad impression sales. In this paper, we strive to study the publisher’s strategy on the reserve price and probe its impact on his/her revenues. We first discuss the reserve price of ad impression in a single-channel sales model, including the online RTB channel or the off-line direct channel, aimed to study its impact on the publisher’ revenue. Then, we further analyze the impact of the reserve price in the multi-channel settings. Finally, we conduct experiments using empirical log data collected from real-world RTB markets to validate our models and analyses, and the experimental results indicate that: 1) in the single-channel sales model, publishers should set the reserve price for only the online-channel ad impressions while not for the off-line-channel ones and 2) in the multi-channel ad impression sales, publishers should set both off-line and online reserve prices for revenue maximization.
      PubDate: June 2018
      Issue No: Vol. 5, No. 2 (2018)
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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