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Authentic chatter

Author

Listed:
  • Bruce Forrester

    (Command Control and Intelligence, Defence Research and Development Canada)

Abstract

This operations research aims to derive an easy but meaningful method for practitioners to identify key influencers and uncover suppressed narratives within a Twitter topic group. This research employs a new concept called “authentic chatter” (analogous to a grass-roots discourse) in combination with influence metrics, content analysis, and commercial-off-the-shelf social media analysis software (NexaIntelligence). The mixed-method exploits the power of social network analysis to determine a small but prominent group of influencers that provides a manageable dataset for the qualitative review of the content. This paper reviews research on social influence and identifies two local influence theories, “indegree” and “retweet”, ideal for topical discussion. Next it reviews Twitter content analysis research looking at specific details on methods. Findings from this past research guide development of a new methodology. The research concludes that use of a prominent group and filtering for authentic chatter increased the signal to noise ratio highlighting important underlying themes within the topic.

Suggested Citation

  • Bruce Forrester, 2020. "Authentic chatter," Computational and Mathematical Organization Theory, Springer, vol. 26(4), pages 382-411, December.
    • Handle: RePEc:spr:comaot:v:26:y:2020:i:4:d:10.1007_s10588-019-09299-0
    DOI: 10.1007/s10588-019-09299-0
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    References listed on IDEAS

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    1. Cynthia Chew & Gunther Eysenbach, 2010. "Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-13, November.
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