A mixed methods model for analyzing professional discourse on Twitter: A content analysis of the #openeducation Hashtag

Citation

Baker, F., & Lowenthal, P. R. (in press). A mixed methods model for analyzing professional discourse on Twitter: A content analysis of the #openeducation Hashtag. International Journal of Social Media and Interactive Learning Environments.

Abstract

Professionals and academics now use social networking sites like Twitter for scholarly discourse around resources and networking. Adding hashtags to tweets allows users to connect with previously unknown others around areas of common interest and provides opportunities to examine these connections. This study explored how open education is discussed on Twitter around the #openeducation hashtag through a scalable mixed methods content analysis model useful for the multi-pronged analyze of hashtag discourse. Researchers analyzed a convenience sample of 903 tweets using the #openeducation hashtag and grouped the results into themes. Thirty-two themes emerged, which were grouped into eight categories. To extend the research model, a questionnaire developed from the themes was piloted with a subset of active hashtag users. The results provide insight into the major discourse on open education, as well as a scalable means to analyze discourse on Twitter, identify active participants, and probe further about ties people have to a topic of interest.

Keywords: Content Analysis; Twitter; Social Media; Open Education

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