Generalizing from social media data: a formal theory approach

Jenny L. Davis*, Tony P. Love

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    28 Citations (Scopus)

    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
    Publication statusPublished - 16 Apr 2019

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