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Retweeting Risk Communication: The Role of Threat and Efficacy

  • Sarah C. Vos
  • , Jeannette Sutton
  • , Yue Yu
  • , Scott Leo Renshaw
  • , Michele K. Olson
  • , C. Ben Gibson
  • , Carter T. Butts

Research output: Contribution to journalArticlepeer-review

71 Scopus citations

Abstract

Social media platforms like Twitter and Facebook provide risk communicators with the opportunity to quickly reach their constituents at the time of an emerging infectious disease. On these platforms, messages gain exposure through message passing (called “sharing” on Facebook and “retweeting” on Twitter). This raises the question of how to optimize risk messages for diffusion across networks and, as a result, increase message exposure. In this study we add to this growing body of research by identifying message-level strategies to increase message passing during high-ambiguity events. In addition, we draw on the extended parallel process model to examine how threat and efficacy information influence the passing of Zika risk messages. In August 2016, we collected 1,409 Twitter messages about Zika sent by U.S. public health agencies’ accounts. Using content analysis methods, we identified intrinsic message features and then analyzed the influence of those features, the account sending the message, the network surrounding the account, and the saliency of Zika as a topic, using negative binomial regression. The results suggest that severity and efficacy information increase how frequently messages get passed on to others. Drawing on the results of this study, previous research on message passing, and diffusion theories, we identify a framework for risk communication on social media. This framework includes four key variables that influence message passing and identifies a core set of message strategies, including message timing, to increase exposure to risk messages on social media during high-ambiguity events.

Original languageEnglish
Pages (from-to)2580-2598
Number of pages19
JournalRisk Analysis
Volume38
Issue number12
DOIs
StatePublished - Dec 2018

Bibliographical note

Publisher Copyright:
© 2018 Society for Risk Analysis

Funding

This research was support by grants from the National Science Foundation (CMMI-1536347; CMMI-1536319). The views presented here represent the views of the authors, not the National Science Foundation.

FundersFunder number
National Science FoundationCMMI-1536347, CMMI-1536319

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • Efficacy
    • risk communication
    • social media
    • threat

    ASJC Scopus subject areas

    • Safety, Risk, Reliability and Quality
    • Physiology (medical)

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