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Assimilate or Differentiate? Contributors’ Choice of Subjects in User‐Generated Content
Author(s) -
Ke Zhihong,
Liu De,
Gupta Alok,
Brass Daniel Joseph
Publication year - 2020
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/deci.12410
Subject(s) - content (measure theory) , ceteris paribus , subject (documents) , preference , diversity (politics) , user generated content , computer science , psychology , social psychology , world wide web , mathematics , statistics , political science , microeconomics , economics , law , mathematical analysis , social media
A key to the content diversity on user‐generated content platforms is what subject users choose to contribute on. This research investigates how two factors can shape contributors’ subject choice decisions, namely, the amount of existing content and content contributed by online friends or “friend content.” Our experimental findings show that both the amount of existing content and friend content can shape a contributor's subject choice decisions: ceteris paribus, contributors prefer subjects with less existing content and ones with friend content when the amount of existing content is the same. In addition, contributors’ preference for subjects with friend content weakens as the amount of existing content on other subject's decreases. Our findings hold important implications for research and practice in user‐generated content platforms and beyond.