Tweeting to the Target: Candidates’ Use of Strategic Messages and @Mentions on Twitter

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


This paper reports on a mixed-methods (i.e., content analysis, machine learning, and quantitative analysis) study of Twitter use among 74 U.S. gubernatorial candidates during the 2014 election. In extending the theory of controlled interactivity, this article focuses on politicians’ use of the @mention where we detail differing messaging strategies when candidates mention themselves versus their opponents, and between incumbents and challengers. Results suggest that candidates use the @mention feature as a subtle audience targeting mechanism. Our work also offers a methodological contribution by showing that machine-learning models perform better when context variables are included.

Original languageEnglish (US)
Pages (from-to)3-18
Number of pages16
JournalJournal of Information Technology and Politics
Issue number1
StatePublished - Jan 2 2018


  • Twitter
  • analysis
  • machine learning
  • political elections
  • strategic messages

ASJC Scopus subject areas

  • General Computer Science
  • Sociology and Political Science
  • Public Administration


Dive into the research topics of 'Tweeting to the Target: Candidates’ Use of Strategic Messages and @Mentions on Twitter'. Together they form a unique fingerprint.

Cite this