Using computational techniques to study social influence online. (September 2020)

• Record Type: Journal Article
• Authors: Cork, Alicia; Everson, Richard; Levine, Mark; Koschate, Miriam
• Other Names: Hopthrow Tim guest-editor.; Smith Laura G. E. guest-editor.; Levine Mark guest-editor.
• Is Part Of: Group processes and intergroup relations. Volume 23:Number 6(2020)
• Page Start: 808
• Page End: 826
• Publication Date: 2020-09
• Subjects: computational social science -- identity prototype -- machine learning -- online social influence -- social identity theory; Intergroup relations -- Periodicals; Social groups -- Periodicals; 302.305
• DOI: 10.1177/1368430220937354
• Languages: English
• ISSNs: 1368-4302

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.