How do you perceive this author? Understanding and modeling authors' communication quality in social media

PLoS One. 2018 Feb 1;13(2):e0192061. doi: 10.1371/journal.pone.0192061. eCollection 2018.

Abstract

In this study, we leverage human evaluations, content analysis, and computational modeling to generate a comprehensive analysis of readers' evaluations of authors' communication quality in social media with respect to four factors: author credibility, interpersonal attraction, communication competence, and intent to interact. We review previous research on the human evaluation process and highlight its limitations in providing sufficient information for readers to assess authors' communication quality. From our analysis of the evaluations of 1,000 Twitter authors' communication quality from 300 human evaluators, we provide empirical evidence of the impact of the characteristics of the reader (demographic, social media experience, and personality), author (profile and social media engagement), and content (linguistic, syntactic, similarity, and sentiment) on the evaluation of an author's communication quality. In addition, based on the author and message characteristics, we demonstrate the potential for building accurate models that can indicate an author's communication quality.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Authorship*
  • Communication*
  • Humans
  • Social Media*

Grants and funding

This work was supported by National Research Foundation of Korea (received by Kyungsik Han), Funding number (2017R1C1B5017391). No URL is available. And by Ajou University (received by Kyungsik Han), Funding number (S-2017-G0001-00040). No URL is available. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.