DETECTING ANTISOCIAL NORMS IN LARGE-SCALE ONLINE DISCUSSIONS

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

This chapter develops a theoretical framework for investigating social norms in online discussions and applies it to study antisocial commenting in two datasets ten years apart. The thesis is that antisocial commenting is promoted through at least two different social processes. First, discussion contributors mimic one another, deploying antisocial comments after other contributors have done so. Second, contributors are responsive to “votes” of approval that they have received for prior instances of antisocial commenting. These two processes map onto a distinction made in the literature on social norms between descriptive and injunctive norms, and this analysis investigates both processes at the individual and collective levels. The chapter compares human annotations of antisocial commenting with several automated classifiers and provides evidence that the classifiers are well-suited for understanding the norms associated with antisocial online commenting. The framework can be applied to online discussions at scale and makes use of both the relational and temporal aspects of the digital trace data that are generated when people use the web and social media.

Original languageEnglish (US)
Title of host publicationSocial Processes of Online Hate
PublisherTaylor and Francis
Pages220-249
Number of pages30
ISBN (Electronic)9781040121573
ISBN (Print)9781032750477
DOIs
StatePublished - Jan 1 2024

ASJC Scopus subject areas

  • General Arts and Humanities
  • General Social Sciences
  • General Computer Science

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