Using computational techniques to study social influence online

Alicia Cork, Miriam Koschate, Mark Levine, Richard Everson

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The social identity approach suggests that group prototypical individuals have greater influence over fellow group members. This effect has been well-studied offline. Here, we use a novel method of assessing prototypicality in naturally occurring data to test whether this effect can be replicated in online communities. In Study 1a (N = 53,049 Reddit users), we train a linguistic measure of prototypicality for two social groups: libertarians and entrepreneurs. We then validate this measure further to ensure it is not driven by demographics (Study 1b: N = 882) or local accommodation (Study 1c: N = 1,684 Silk Road users). In Study 2 (N = 8,259), we correlate this measure of prototypicality with social network indicators of social influence. In line with the social identity approach, individuals who are more prototypical generate more responses from others. Implications for testing sociopsychological theories with naturally occurring data using computational approaches are discussed.
Original languageEnglish
Pages (from-to)808
Number of pages826
JournalGroup Processes and Intergroup Relations
Volume23
Issue number6
DOIs
Publication statusPublished - 30 Sep 2020

Keywords

  • computational social science
  • identity prototype
  • machine learning
  • online social influence
  • social identity theory
  • natural language processing

ASJC Scopus subject areas

  • Social Psychology

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