Generalizing from social media data: a formal theory approach

Jenny L. Davis, Tony P. Love

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

Researchers increasingly draw on social media data to answer big questions about social patterns and dynamics. However, as with any data source, social media data present both opportunities and significant challenges. One major critique of social media data is that the data are not generalizable outside of the platforms from which the data originate. Problems of generalizability stem from non-universal participation rates on various platforms, demographically biased samples, as well as limited access to data based on infrastructural constraints and/or user privacy practices. We suggest that instead of empirical generalizability, social media data are theoretically generalizable in the formal theory tradition. Through a case example in which we use YouTube comments to test and extend a key tenet of identity theory, we show how social media data can instantiate theoretical variables and thus generalize to theoretical propositions. Mediated through formal theory, social media data maintain the capacity to address broad social questions while upholding methodological integrity.

Original languageEnglish
Pages (from-to)637-647
Number of pages11
JournalInformation Communication and Society
Volume22
Issue number5
DOIs
StatePublished - Apr 16 2019

Bibliographical note

Publisher Copyright:
© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • Generalizability
  • big data
  • formal theory
  • research methods
  • social media

ASJC Scopus subject areas

  • Communication
  • Library and Information Sciences

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