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Retweeting Risk Communication: The Role of Threat and Efficacy

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

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.

Suggested Citation

  • Sarah C. Vos & Jeannette Sutton & Yue Yu & Scott Leo Renshaw & Michele K. Olson & C. Ben Gibson & Carter T. Butts, 2018. "Retweeting Risk Communication: The Role of Threat and Efficacy," Risk Analysis, John Wiley & Sons, vol. 38(12), pages 2580-2598, December.
  • Handle: RePEc:wly:riskan:v:38:y:2018:i:12:p:2580-2598
    DOI: 10.1111/risa.13140
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    References listed on IDEAS

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    1. Bail, C.A., 2016. "Emotional feedback and the viral spread of social media messages about autism spectrum disorders," American Journal of Public Health, American Public Health Association, vol. 106(7), pages 1173-1180.
    2. Rajagopal, 2013. "Social Media Metrics," Palgrave Macmillan Books, in: Managing Social Media and Consumerism, chapter 7, pages 132-151, Palgrave Macmillan.
    3. Larry G. Epstein, 1999. "A Definition of Uncertainty Aversion," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 66(3), pages 579-608.
    4. Seth M. Noar & Benjamin M. Althouse & John W. Ayers & Diane B. Francis & Kurt M. Ribisl, 2015. "Cancer Information Seeking in the Digital Age," Medical Decision Making, , vol. 35(1), pages 16-21, January.
    5. Harris, J.K. & Mueller, N.L. & Snider, D., 2013. "Social media adoption in local health departments nationwide," American Journal of Public Health, American Public Health Association, vol. 103(9), pages 1700-1707.
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    Cited by:

    1. Ying Lian & Yueting Zhou & Xueying Lian & Xuefan Dong, 2022. "Cyber violence caused by the disclosure of route information during the COVID-19 pandemic," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-18, December.
    2. Han Lv & Xueyan Cao & Shiqi Chen & Liqun Liu, 2022. "Public and Private Information Sharing under “New Normal” of COVID-19: Understanding the Roles of Habit and Outcome Expectation," IJERPH, MDPI, vol. 19(9), pages 1-26, May.

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