On the Social Influence in Human Behavior: Physical, Homophily, and Social Communities

Luceri, Luca; Vancheri, Alberto; Braun, Torsten; Giordano, Silvia (December 2017). On the Social Influence in Human Behavior: Physical, Homophily, and Social Communities. In: 6th International Conference of Complex Networks and their Application. Studies in Computational Intelligence: Vol. 689 (pp. 856-868). Springer 10.1007/978-3-319-72150-7_69

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Understanding the forces governing human behavior and social dynamics is a challenging and unsolved problem. Individuals’ decisions and actions are affected by interlaced factors, such as physical location, homophily, and social ties. In this paper, we investigate the impact of these factors on human behavior. In particular, we propose to examine the role that distinct communities play as sources of social influence. The traditional approach in literature is to use direct social relationships among subjects to study this phenomenon. Our hypothesis is that individuals are embedded in communities not only related to their direct social relationships, but that involve different and complex forces. We study and analyze physical, homophily, and social communities to evaluate their relation with subjects’ behavior. We prove that social influence is correlated with these communities, and each one of them is (differently) significant for individuals, confirming our hypothesis. To our knowledge, this is the first work that proves such correlations. These findings contribute with valuable input to the comprehension and prediction of human behavior. According to these results, we derive community-based features that reflect the subject involvement in these groups. We use such features with a supervised learning algorithm to predict subject participation in social events, achieving an accuracy of 82%.

Item Type:

Conference or Workshop Item (Paper)


08 Faculty of Science > Institute of Computer Science (INF) > Communication and Distributed Systems (CDS)
08 Faculty of Science > Institute of Computer Science (INF)

UniBE Contributor:

Braun, Torsten


000 Computer science, knowledge & systems
500 Science > 510 Mathematics


Studies in Computational Intelligence






Dimitrios Xenakis

Date Deposited:

30 May 2017 16:22

Last Modified:

01 May 2020 10:47

Publisher DOI:






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