Functional and emotional traits of corporate social media message strategies: Behavioral insights from S&P 500 Facebook data

Yi Grace Ji, Zifei Fay Chen, Weiting Tao, Zongchao Cathy Li

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

Drawing from literature regarding public engagement, the Elaboration Likelihood Model (ELM), computer-mediated communication research, and emotion psychology, this study examines the effects of companies’ social media communication strategies on public engagement behaviors as indexed by post likes, shares, and comments. Specifically, it investigates how corporate Facebook posts’ functional traits (functional interactivity and vividness) and emotional traits (emotion presence, valence, and strength) impact public engagement online. Through data mining and computer-assisted sentiment analysis of 33,379 posts from 106 Standard & Poor 500 companies’ Facebook accounts, this study finds a negative effect of functional interactivity but a positive effect of vividness on engagement. It also shows that emotional traits overall yield stronger public engagement outcomes. Two-way interactions between emotional and functional features are also detected. Theoretical and practical implications are discussed.

Original languageEnglish (US)
JournalPublic Relations Review
DOIs
StateAccepted/In press - Jan 1 2018

Keywords

  • Computer-assisted sentiment analysis
  • Elaboration Likelihood Model
  • Emotion
  • Functional interactivity
  • Message strategies
  • Social media engagement
  • Vividness

ASJC Scopus subject areas

  • Communication
  • Organizational Behavior and Human Resource Management
  • Marketing

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