Authentic chatter
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Authentic chatter Bruce Forrester1
© Crown 2019
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. Keywords Authentic chatter · Social network analysis · Content analysis · Mixedmethod · Twitter analysis
1 Introduction Western government and military organizations have just recently started to realize the importance of social media as a way to both communicate with and listen to populations. Unfortunately this late start has left them at a disadvantage to those countries which have been, for many years, exploiting social media in order to influence and divide the public opinion of rival countries. As a result of this late start, the expertise to search, filter, and make sense of large numbers of tweets resides mainly with scientists and researchers in academia or government labs and not with * Bruce Forrester bruce.forrester@drdc‑rddc.gc.ca 1
Command Control and Intelligence, Defence Research and Development Canada, Quebec City, Canada
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the public affairs officers or analysts. Fortunately there is a vibrant research community that use Social Network Analysis (SNA) as well as mixed-methods that can be drawn upon for knowledge. This paper will examine the research behind these methods with the objective to derive a simplified methodology that can be employed by non-expert personnel in order to uncover narratives and to be able to react to large collections of tweets. SNA theories are elegant and sophisticated; however, they can be hard to understand and are not necessarily designed to expose an in-depth appreciation of the content of tweets. Notwithstanding, they are ideal to identify groups of users especially those authors whom are influential. For a deep understanding of the content, incorporation of both quantitative filtering and qualitative content analysis methods will be added to round out the proposed methodology. Assuming that our government analysts and public affairs personnel are not generally scientists, sta
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