Abstract: Social relations and multigenerational networks remain a salient fixture of American Indian (AI) culture and survivance. Network data can describe the dynamic nature of social networks and the powerful role these relationships play in the development of behaviors in adolescence. Research in other populations has demonstrated how networks impact risk and resilience, but data on these factors are lacking among AI adolescents. There are reasons to expect that network structures may differ and that prevailing social network theories may not apply among this population. This paper describes ego and grade level networks of 9th and 10th grade AI youth (N = 263) in three diverse schools on a Northern Plains reservation. Aligned with prior research, we find that gender homophily plays a role in friendship formation. Unlike in other settings, race/ethnicity was not a significant predictor of friendship ties; this finding is not surprising given that 94% of the sample identified as being from this Northern Plains tribe. The descriptive findings also suggest that AI youth have a significant portion of family ties, even among their school-based networks. This may be a distinct feature of AI networks. Variation in networks across schools suggests unique community contexts that may make a universal approach to prevention development and implementation less effective. Within this tribal community, we find significant differences in the types, sizes, and potential mechanisms of tie formation. This underscores the importance of identifying network variations to implement targeted preventive interventions for feasibility, efficacy, and sustainability. PubDate: Mon, 22 Jul 2024 00:00:00 GMT
Abstract: Vennmaker software was created as a tool for actor-centered and interactive networks. It has many options that users can implement at different stages of their studies. Documentation is available showing how to use it technically and the steps to follow for its correct use. However, less has been documented about the experience of using it in fieldwork to establish personal networks, a gap which this article aims to fill. This article combines the experiences of doing fieldwork using Vennmaker in two very different contexts and research designs. It concentrates on its advantages and disadvantages, as well as its usefulness in learning, while also sharing some useful information for those who are planning to use it in future research. PubDate: Sat, 20 Jul 2024 00:00:00 GMT
Abstract: Despite a rapid increase in research on the underpinnings of misinformation susceptibility, scholars still disagree about the relative impacts of social context and individual cognitive factors. We argue that cognitive reflection and identity-based network homogeneity may have unique influences on different types of misinformation. Specifically, identity-based network homogeneity predicts bias that is related to any type of identity-based information (i.e., political rumors), and cognitive reflection is more tailored toward truth discernment (i.e., fake news headlines). We conducted our study using an online sample (N = 214) split evenly between Democrats and Republicans and collected data on personal network composition, cognitive reflection, as well as susceptibility, sentiments, and sharing behavior in relation to political rumors and misinformation, respectively. Results demonstrate that where network homogeneity predicts belief and sharing in both political rumors and fake news headlines, cognitive reflection only predicts belief and sharing of fake news headlines. Social vs. cognitive factors for predicting different types of misinformation are discussed. PubDate: Fri, 28 Jun 2024 00:00:00 GMT
Abstract: Fractals describe structural details at arbitrarily small scales, but are mathematically not necessarily complex, presenting a pragmatic way of describing nature. They are also common in social settings, including the organizational space. However, attention has been devoted to temporal fractal patterns in heterarchical or networked organizations. This article leverages data on face-to-face interactions collected by the SocioPatterns collaboration in a public sector organization to investigate temporal fractal patterns in interaction networks and three types of processes have been identified in this. White noise exhibits no correlation in time with rapid, chaotic changes. Brown noise entails a diffusion process with stable, structural patterns, but no quick adaptation. Pink noise exhibits an equilibrium between the two, producing dynamics that maintain stable patterns of interactions, remaining flexible to regulate interaction. The interaction network is described with metrics of social network analysis, and analyzed with detrended fluctuation analysis (DFA) to detect temporal fractal patterns within the three largest departments as well as the whole organization. Results indicate high levels of pink noise with traces of white noise in the departments as well as pink noise with traces of brown noise on the organizational level. While previous research found pink noise processes in self-organizing networks, this article extends them to structured intraorganizational networks. The low levels of brown noise question the influence of rigid organizational structures and processes on the temporal structure of interaction. Hence, the fractal temporal structure of the interactions themselves is a factor that contributes to the stability of interactions between individuals over time. PubDate: Wed, 29 May 2024 00:00:00 GMT
Abstract: Problem-solving effectiveness is key to organizational performance. To solve problems, gathering information from colleagues is critical, and positioning brokerage in communication networks is beneficial. The communication network for problem-solving is formed depending on the nature of the problem. Thus, the problem-solving network is the relational event network, and the connection of the problem-solving network dynamically changes over time depending on the problem basis. This study investigates the dynamics of brokerage in a problem-solving network and its impact on productivity in a company that provides technical support and troubleshooting for the IT system that its corporate customers use. By exploiting high-frequency data on face-to-face communication among employees collected by wearable sensors, we established the following results. First, the communication partners of each employee change weekly, which is a reasonable time to solve problems in the company. Second, with the change in the communication network, employees who position brokerage also change on a weekly basis. Third, while brokerage in a week has a positive impact on employee performance during the week, it has no impact on employee performance in the following week. PubDate: Wed, 29 May 2024 00:00:00 GMT
Abstract: The integration of digital technology in modern society has led to an increased importance of the analysis of the digital environment in political elections. The concept of echo chambers and their influence on social networks has received significant attention in recent academic investigations. Echo chambers are commonly referred to as the digital bubble where users participate in a conversation mostly with like-minded others, and it is usually related not only to homophily but can also be directly associated with the effects of social media algorithms. This study examines the Twitter interactions during two Spanish regional elections. Data collection has been performed through Twitter Streaming API, which resulted in a total dataset of 5.5 million tweets. The study analyzes how the political communities interact inside and between them. Also, we replicate this analysis by grouping the political communities by two main affinity blocks (left-right) to evaluate if the effects of homophily are even higher under this hypothesis. Finally, the text of the tweets was analyzed to reinforce the community-interaction analysis and to conduct a sentiment analysis of the interactions. The research results indicate that within each political party community, interactions predominantly occur among individuals who hold similar political views, leading to the creation of echo chambers. These echo chambers become even more powerful when parties are unified into political affinity blocks, with over 97% of interactions occurring within each left-right block. This study aims to contribute to the ongoing academic debate by providing relevant data and reinforcing aspects studied by previous researchers. PubDate: Sat, 18 May 2024 00:00:00 GMT
Abstract: Over the last thirty years, in parallel with the global uptake of the world wide web, social network analysis (SNA) has become a significant analytical approach within several disciplines and it currently holds a prominent position in academic discussions across a diverse range of topics. This special theme of Connections, the journal of the International Network for Social Network Analysis, adds to the rapidly growing body of network research with a focus on exploring the principle of homophily in social networks. It presents 5 studies from a selected number of participants to the symposium “Similarity, Selection and Influence: A Cross-Disciplinary Symposium on Homophily in Social Networks” (7–8 July, 2022, Groningen, the Netherlands). Taken together, the special theme provides an interdisciplinary understanding of homophily in social networks and outlines avenues for future research to keep investigating the subject. PubDate: Sat, 18 May 2024 00:00:00 GMT
Abstract: The development of the “public sphere” and the Enlightenment are closely related to the networks of publishers involved in print culture. In Britain, a key question is whether diversity (in terms of nationality) in publishing increased over time. In this paper, we use large-scale library catalog data and a class of models known as Exponential Random Graph Models (ERGMs) to investigate the extent to which an 18th-century network of publishers in London was homophilous with respect to nationality, and specifically investigate whether those with close publishing connections to Scotland formed a separate group or if they were simply integrated into the London book market. As there is little external information on the majority of publishers, we generate node and edge attributes from the catalog data itself. The results suggest that social processes were deeply involved in the decisions behind copublishing and collaborations and that there is indeed a significant positive effect on tie formation if both nodes are “Scottish” publishers, though this lessens over the century. We find that other important factors in tie formation are edgewise shared partners and similarity in patterns of genres published. PubDate: Sat, 18 May 2024 00:00:00 GMT
Abstract: This study analyses the frame resonance in the Twitter debate of Gustavo Petro and, especially, of Francia Márquez’s rhetoric during the presidential elections campaign of 2022. I specifically study the potential resonance of the notion of Otherness in tweets attributed to women and to men. I apply several methodological protocols including network analysis and topic modeling. The results are positive on the frame resonance of the campaign and Francia Márquez rhetoric in both groups, showing ideological-political engagement from a semantic view more than a gendered connection. However, semantic relatedness to the particular framing studied here appears to be stronger in women than in men. Addressing Twitter attributes such as mentions and hashtags is similar in both groups. PubDate: Sat, 18 May 2024 00:00:00 GMT
Abstract: This paper examines the dissemination of Cartesianism in the 17th century by studying the networks of authors in the field of natural philosophy. Key figures who spread knowledge and innovated the field are identified and contextualized. Furthermore, the network analysis shows how different ways of thinking coexisted within the social networks of early modern natural philosophers. To achieve this methodologically, originally bipartite networks were projected into author-to-author networks that were divided into time slices. Measurements of centrality and assortativity were used to determine prominence and diversity, which were complemented and refined with close reading. The findings reveal not only cliques of geographically connected authors, but also an overall highly connected field. Additionally, assortativity indicates a moderate tendency toward homophily in the authors’ connections to others within the same philosophical tradition. The study furthermore identifies that central authors were predominantly eclectic or Cartesian, suggesting that Cartesianism was driven by such individuals in structurally well-connected positions. PubDate: Sat, 18 May 2024 00:00:00 GMT
Abstract: Most recent academic studies of homophily—the tendency of people to interact with similar others—lean to a sociological critique of digital technologies, rather than revealing fundamentally positive outcomes. A few solid philosophical endeavors have emerged from the fields of philosophy of technology and enactive ethics. This article adopts a sociological perspective to argue that digital social networks can serve as an ethical infrastructure for facilitating effective communication. However, they also face the challenge of organizing the myriad of individual voices present within them, so that the necessary moral conditions to mitigate homophily can be established. From this viewpoint, it is suggested homophily should be viewed not as an individual’s right to expression but as a cultivated echo-moral cultured landscape. Homophily is not an input but an outcome. Homophily does not happen without evaluating reception. A voice without assessment lacks the ethical dimension. By applying the theory of the social construction of reality (Berger & Luckmann, 2008), homophily can be conceived as the contribution of significant others. Most importantly, effective communication can be attained when new secondary institutions organize the input of significant others into a meaningful generalized other (Mead, 2015). As a result, I propose that digital technologies allow for ameliorating the moral character of the individual by shifting how one looks at communication: from an individual’s right to a voice into an ordered culture of voices, from preserving rights to serving rightly. This perspective could illuminate policymakers to establish right processes to avoid homophily and help individuals and organizations achieve effective means of communication and deliberation. PubDate: Sat, 18 May 2024 00:00:00 GMT
Abstract: The fields of social network analysis and network science have recently undertaken efforts to address issues of gender diversity and representation. However, despite these important efforts, subtle threats to representation are likely to persist. I use a 2023 global survey of 260 network researchers to show that men rate themselves as having more expertise with networks than women. This is troubling because, to the extent that women believe they lack the expertise to be considered for awards or collaboration opportunities, it can impede other efforts to diversify the field. I conclude by discussing some possible explanations for this finding and some possible strategies for addressing its consequences. PubDate: Tue, 29 Aug 2023 00:00:00 GMT
Abstract: Variationist studies have shown the implication of tie properties in the emergence and preservation of linguistic norms. This contribution deepens the understanding of this mechanism at the dyadic level. It explores relational subjectivity and relativity among individuals of a community and their implications in the distribution of lexical variants. The aim is to understand how the reciprocity of a relation influences the share of lexical practices. To do so, we analyze the network of discussions of bachelor's degree students of the University of Geneva and their lexical practices. Using the modern methods used in social network analysis to study relational properties and by running multiple regression quadratic assignment procedure (MRQAP), reciprocal interactions are found to lead to a higher lexical share and similarity. PubDate: Fri, 10 Mar 2023 00:00:00 GMT
Abstract: Satisfaction with any aspect of life is not easy to defined, and sometimes, it is still a topic of discussion. That is especially relevant for more excluded populations like older people. This research looked into how relevant the social support networks (SSNs) of older people are for their satisfaction with retirement, specifically in the Chilean context. It will identify some sufficient and necessary conditions for older people to be satisfied with retirement. This research focuses on 30 life histories of older people in Santiago, Chile. They were asked about their histories and SSNs. The analysis applied used a Qualitative Comparative Analysis (QCA) with conditions from the Social Network Analysis (SNA). The results identify sufficient and necessary conditions to achieve satisfaction with retirement. It is highlighted some of the dimensions of SSNs and their reciprocities as relevant conditions for satisfaction with retirement. PubDate: Tue, 28 Feb 2023 00:00:00 GMT
Abstract: This brief article illustrates the features of ScriptNet, a software package that facilitates a visual analysis of the organisational aspects of criminal enterprise, together with a visual analysis of the network of people, organisations, places and resources that are in some way involved in the commissioning of these goal-oriented crimes. ScriptNet is an amalgamation of the terms ‘script’ and ‘network’ that in turn represent two analytical approaches to understanding criminal and social behaviours. Script refers to crime script analysis, an analytical technique that organises knowledge about the procedural aspects and procedural requirements of the crime commission process. Network derives from social network analysis, and specifically from the framework of multi-mode and multi-link networks, which maps individual and collective actors, together with resources they can access and places where they are located, and the various types of relationships that may link them. In this article we illustrate the functions and features of ScriptNet using data provided by the Food Safety Authority of Ireland (FSAI). We discuss the innovative aspects of ScriptNet and we identify its limits. In its current format, ScriptNet has been developed as proof of concept. The code is open source, and we welcome people to collaborate and implement new and improved functions. PubDate: Fri, 28 Oct 2022 00:00:00 GMT
Abstract: Isolation and cohesion are two key network features, often used to predict outcomes like mental health and deviance. More cohesive settings tend to have better outcomes, while isolates tend to fare worse than their more integrated peers. A common assumption of past work is that the effect of cohesion is universal, so that all actors get the same benefits of being in a socially cohesive environment. Here, we suggest that the effect of cohesion is universal only for specific types of outcomes. For other outcomes, experiencing the benefits of cohesion depends on an individual’s position in the network, such as whether or not an individual has any social ties. Network processes thus operate at both the individual and contextual level, and we employ hierarchical linear models to analyze these jointly to arrive at a full picture of how networks matter. We explore these ideas using the case of adolescents in schools (using Add Health data), focusing on the effect of isolation and cohesion on two outcomes, school attachment and academic engagement. We find that cohesion has a uniform effect in the case of engagement but not attachment. Only non-isolates experience stronger feelings of attachment as cohesion increases, while all students, both isolates and non-isolates, are more strongly engaged in high cohesion settings. Overall, the results show the importance of taking a systematic, multi-level approach, with important implications for studies of health and deviance. PubDate: Fri, 28 Oct 2022 00:00:00 GMT
Abstract: Political network data can often be challenging to collect and clean for analysis. This article demonstrates how the incidentally and backbone packages for R can be used together to construct networks among legislators in the US Congress. These networks can be customized to focus on a specific chamber (Senate or House of Representatives), session (2003 to present), legislation type (bills and resolutions), and policy area (32 topics). Four detailed examples with replicable code are presented to illustrate the types of networks and types of insights that can be obtained using these tools. PubDate: Fri, 14 Oct 2022 00:00:00 GMT
Abstract: The effect of leadership decapitation—the capture or killing of the leader of an armed group—on future violence has been studied with competing conclusions. In Mexico, leadership decapitation has been found to increase violence and in-fighting among drug cartels. However, the causal pathways between leadership decapitation and in-fighting are unclear. In this article, it is hypothesized that leadership decapitation will weaken alliances between armed actors, lead to greater preferential attachment in networks of cartels and militias, and result in greater transitive closure as cartels seek to expand their power. These hypotheses are tested with a stochastic actor oriented model on a network dataset of episodes of infighting among cartels and the militias formed to opposed them between the five years before and after Joaquín, “El Chapo” Guzmán Loera, the former leader of the Sinaloa Cartel, was arrested in 2016. The results show that alliances have virtually no effect on the decision of cartels and militias to fight each other; weaker organizations faced a higher reputational cost after El Chapo’s detention; and post-arrest cartel in-fighting did not increase as a result of uncertainty about the relative balance of power among cartels. PubDate: Sat, 06 Nov 2021 00:00:00 GMT
Abstract: A cohesive network keeps groups together and enables members to communicate about and cooperate for public goods. For ongoing cooperation, group members have to know if their group members cooperate or defect, but this information—mostly through gossip—is threatened by noise and biases. If there are redundant information channels, however, errors in monitoring and transmission in one imperfect channel can, to some degree, be corrected by information through another imperfect channel, and may lead to higher levels of cooperation. An influential conceptualization of social cohesion based on redundancy is K-connectivity: the minimum number (K) of node-independent paths connecting pairs of nodes in a group’s network. In a lab experiment, we tested if higher K-connectivity yields higher levels of cooperation for public goods, controlling for a number of other network effects such as density, size, and average distance. We do not find the hypothesized effect, which might be due to a not-earlier-found shortcoming of the concept, and we propose a solution. PubDate: Fri, 05 Feb 2021 00:00:00 GMT
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