Community Structure Characterization

This entry discusses the problem of describing some communities identified in a complex network of interest, in a way allowing to interpret them. We suppose the community structure has already been detected through one of the many methods proposed in the literature. The question is then to know how to extract valuable information from this first result, in order to allow human interpretation. This requires subsequent processing, which we describe in the rest of this entry

The co-evolution of emotional well-being with weak and strong friendship ties

Social ties are strongly related to well-being. But what characterizes this relationship? This study investigates social mechanisms explaining how social ties affect well-being through social integration and social influence, and how well-being affects social ties through social selection. We hypothesize that highly integrated individuals - those with more extensive and dense friendship networks - report higher emotional well-being than others. Moreover, emotional well-being should be influenced by the well-being of close friends. Finally, well-being should affect friendship selection when individuals prefer others with higher levels of well-being, and others whose well-being is similar to theirs. We test our hypotheses using longitudinal social network and well-being data of 117 individuals living in a graduate housing community. The application of a novel extension of Stochastic Actor-Oriented Models for ordered networks (ordered SAOMs) allows us to detail and test our hypotheses for weak- and strong-tied friendship networks simultaneously. Results do not support our social integration and social influence hypotheses but provide evidence for selection: individuals with higher emotional well-being tend to have more strong-tied friends, and there are homophily processes regarding emotional well-being in strong-tied networks. Our study highlights the two-directional relationship between social ties and well-being, and demonstrates the importance of considering different tie strengths for various social processes

Community structure and patterns of scientific collaboration in Business and Management

This is the author's accepted version of this article deposited at arXiv (arXiv:1006.1788v2 [physics.soc-ph]) and subsequently published in Scientometrics October 2011, Volume 89, Issue 1, pp 381-396. The final publication is available at link.springer.com http://link.springer.com/article/10.1007%2Fs11192-011-0439-1Author's note: 17 pages. To appear in special edition of Scientometrics. Abstract on arXiv meta-data a shorter version of abstract on actual paper (both in journal and arXiv full pape

Structural Cohesion, Role Equivalence, or Homophily: Which Process Best Explains Social Homogeneity?

Social homogeneity, understood as the similarity of perceptions and attitudes that individuals display toward the environment around them, is explained by the relational context in which they are immersed. However, there is no consensus about which relational mechanism best explains social homogeneity. The purpose of this research is to find out which of the three classical relational processes most studied in network analysis (structural cohesion, role equivalence, or homophily) is more determinant in explaining social homogeneity. To achieve the research objective, 110 professionals (psychologists, social workers, and community facilitators) implementing a psychosocial care program in three regions of Northwest Colombia were interviewed. Different types of relationships among professionals were analyzed using network analysis techniques. To examine the structural cohesion hypothesis, interveners were categorized according to the level of structural cohesion by performing core-periphery analysis in the networks evaluated; to test the role equivalence hypothesis, participants were categorized according to their level of degree centrality in the networks examined; to test the homophily hypothesis, participants were grouped according to the level of homophily in terms of professional profile. The non-parametric tests showed that role equivalence was the most powerful mechanism for explaining social homogeneity in the sample of psychosocial interveners evaluated.Universidad Pontificia Bolivariana 203-01/17/G-003Universidad Tecnológica de Bolivar 2301139

Measuring and mitigating behavioural segregation using Call Detail Records

The overwhelming amounts of data we generate in our daily routine and in social networks has been crucial for the understanding of various social and economic factors. The use of this data represents a low-cost alternative source of information in parallel to census data and surveys. Here, we advocate for such an approach to assess and alleviate the segregation of Syrian refugees in Turkey. Using a large dataset of mobile phone records provided by Turkey's largest mobile phone service operator, Türk Telekom, in the frame of the Data 4 Refugees project, we define, analyse and optimise inter-group integration as it relates to the communication patterns of two segregated populations: refugees living in Turkey and the local Turkish population. Our main hypothesis is that making these two communities more similar (in our case, in terms of behaviour) may increase the level of positive exposure between them, due to the well-known sociological principle of homophily. To achieve this, working from the records of call and SMS origins and destinations between and among both populations, we develop an extensible, statistically-solid, and reliable framework to measure the differences between the communication patterns of two groups. In order to show the applicability of our framework, we assess how house mixing strategies, in combination with public and private investment, may help to overcome segregation. We first identify the districts of the Istanbul province where refugees and local population communication patterns differ in order to then utilise our framework to improve the situation. Our results show potential in this regard, as we observe a significant reduction of segregation while limiting, in turn, the consequences in terms of rent increase

Hazard Exposure Heterophily: A Latent Characteristic in Socio-Spatial Networks Influencing Community Resilience

We present a latent characteristic in socio-spatial networks, hazard-exposure heterophily, to capture the extent to which populations with similar hazard exposure could assist each other through social ties. Heterophily is the tendency of unlike individuals to form social ties. Conversely, populations in spatial areas with significant hazard exposure similarity, homophily, would lack sufficient resourcefulness to aid each other to lessen the impact of hazards. In the context of the Houston metropolitan area, we use Meta's Social Connectedness data to construct a socio-spatial network in juxtaposition with flood exposure data from National Flood Hazard Layer to analyze flood hazard exposure of spatial areas. The results reveal the extent and spatial variation of hazard-exposure heterophily in the study area. Notably, the results show that lower-income areas have lower hazard-exposure heterophily possibly caused by income segregation and the tendency of affordable housing development to be located in flood zones. Less resourceful social ties due to high hazard-exposure homophily may inhibit low-income areas from better coping with hazard impacts and could contribute to their slower recovery. Overall, the results underscore the significance of characterizing hazard-exposure heterophily in socio-spatial networks to reveal community vulnerability and resilience to hazards.Comment: 14 pages, 6 figure

Communities and patterns of scientific collaboration in Business and Management

This is the author's accepted version of this article deposited at arXiv (arXiv:1006.1788v2 [physics.soc-ph]) and subsequently published in Scientometrics October 2011, Volume 89, Issue 1, pp 381-396. The final publication is available at link.springer.com http://link.springer.com/article/10.1007%2Fs11192-011-0439-1Author's note: 17 pages. To appear in special edition of Scientometrics. Abstract on arXiv meta-data a shorter version of abstract on actual paper (both in journal and arXiv full pape

Communities and patterns of scientific collaboration

This is the author's accepted version of this article deposited at arXiv (arXiv:1006.1788v2 [physics.soc-ph]) and subsequently published in Scientometrics October 2011, Volume 89, Issue 1, pp 381-396. The final publication is available at link.springer.com http://link.springer.com/article/10.1007%2Fs11192-011-0439-1Author's note: 17 pages. To appear in special edition of Scientometrics. Abstract on arXiv meta-data a shorter version of abstract on actual paper (both in journal and arXiv full paper17 pages. To appear in special edition of Scientometrics. Abstract on arXiv meta-data a shorter version of abstract on actual paper (both in journal and arXiv full paper version)17 pages. To appear in special edition of Scientometrics. Abstract on arXiv meta-data a shorter version of abstract on actual paper (both in journal and arXiv full paper version)17 pages. To appear in special edition of Scientometrics. Abstract on arXiv meta-data a shorter version of abstract on actual paper (both in journal and arXiv full paper version)17 pages. To appear in special edition of Scientometrics. Abstract on arXiv meta-data a shorter version of abstract on actual paper (both in journal and arXiv full paper version)This paper investigates the role of homophily and focus constraint in shaping collaborative scientific research. First, homophily structures collaboration when scientists adhere to a norm of exclusivity in selecting similar partners at a higher rate than dissimilar ones. Two dimensions on which similarity between scientists can be assessed are their research specialties and status positions. Second, focus constraint shapes collaboration when connections among scientists depend on opportunities for social contact. Constraint comes in two forms, depending on whether it originates in institutional or geographic space. Institutional constraint refers to the tendency of scientists to select collaborators within rather than across institutional boundaries. Geographic constraint is the principle that, when collaborations span different institutions, they are more likely to involve scientists that are geographically co-located than dispersed. To study homophily and focus constraint, the paper will argue in favour of an idea of collaboration that moves beyond formal co-authorship to include also other forms of informal intellectual exchange that do not translate into the publication of joint work. A community-detection algorithm is applied to the co-authorship network of the scientists that submitted in Business and Management in the 2001 UK RAE. While results only partially support research-based homophily, they indicate that scientists use status positions for discriminating between potential partners by selecting collaborators from institutions with a rating similar to their own. Strong support is provided in favour of institutional and geographic constraints. Scientists tend to forge intra-institutional collaborations; yet, when they seek collaborators outside their own institutions, they tend to select those who are in geographic proximity