Social selection and peer influence in an online social network.

Kevin Lewis, Marco Gonzalez, Jason Kaufman
Author Information
  1. Kevin Lewis: Department of Sociology and Berkman Center for Internet and Society, Harvard University, Cambridge, MA 02138, USA.

Abstract

Disentangling the effects of selection and influence is one of social science's greatest unsolved puzzles: Do people befriend others who are similar to them, or do they become more similar to their friends over time? Recent advances in stochastic actor-based modeling, combined with self-reported data on a popular online social network site, allow us to address this question with a greater degree of precision than has heretofore been possible. Using data on the Facebook activity of a cohort of college students over 4 years, we find that students who share certain tastes in music and in movies, but not in books, are significantly likely to befriend one another. Meanwhile, we find little evidence for the diffusion of tastes among Facebook friends-except for tastes in classical/jazz music. These findings shed light on the mechanisms responsible for observed network homogeneity; provide a statistically rigorous assessment of the coevolution of cultural tastes and social relationships; and suggest important qualifications to our understanding of both homophily and contagion as generic social processes.

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MeSH Term

Confidence Intervals
Humans
Internet
Models, Biological
Music
Peer Group
Social Behavior
Social Support
Stochastic Processes
Students

Word Cloud

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