Authentic chatter

Bruce Forrester ()
Additional contact information
Bruce Forrester: Command Control and Intelligence, Defence Research and Development Canada

Computational and Mathematical Organization Theory, 2020, vol. 26, issue 4, No 2, 382-411

Abstract: 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; Mixed-method; Twitter analysis (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10588-019-09299-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:comaot:v:26:y:2020:i:4:d:10.1007_s10588-019-09299-0

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10588

DOI: 10.1007/s10588-019-09299-0

Access Statistics for this article

Computational and Mathematical Organization Theory is currently edited by Terrill Frantz and Kathleen Carley

More articles in Computational and Mathematical Organization Theory from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().