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Cultural carrying capacity: Organ donation advocacy, discursive framing, and social media engagement

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  • Bail, Christopher A.

Abstract

Social media sites such as Facebook have become a powerful tool for public health outreach because they enable advocacy organizations to influence the rapidly increasing number of people who frequent these forums. Yet the very open-ness of social media sites creates fierce competition for public attention. The vast majority of social media messages provoke little or no reaction because of the sheer volume of information that confronts the typical social media user each day. In this article, I present a theory of the “cultural carrying capacity” of social media messaging campaigns. I argue that advocacy organizations inspire more endorsements, comments, and shares by social media users if they diversify the discursive content of their messages. Yet too much diversification creates large, disconnected audiences that lack the sense of shared purpose necessary to sustain an online movement. To evaluate this theory, I created a Facebook application that collects social media posts produced by forty-two organ donation advocacy organizations over 1.5 years, as well as supplemental information about the organization, its audience, and the broader social context in which they interact. Time series models provide strong evidence for my theory net of demographic characteristics of social media users, the resources and tactics of each organization, and broader external factors. I conclude by discussing the implications of these findings for public health, cultural sociology, and the nascent field of computational social science.

Suggested Citation

  • Bail, Christopher A., 2016. "Cultural carrying capacity: Organ donation advocacy, discursive framing, and social media engagement," Social Science & Medicine, Elsevier, vol. 165(C), pages 280-288.
  • Handle: RePEc:eee:socmed:v:165:y:2016:i:c:p:280-288
    DOI: 10.1016/j.socscimed.2016.01.049
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    References listed on IDEAS

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    1. Beck, Nathaniel & Katz, Jonathan N., 1995. "What To Do (and Not to Do) with Time-Series Cross-Section Data," American Political Science Review, Cambridge University Press, vol. 89(3), pages 634-647, September.
    2. Talley, R.C. & Crews, J.E., 2007. "Framing the public health of caregiving," American Journal of Public Health, American Public Health Association, vol. 97(2), pages 224-228.
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    Cited by:

    1. Cao, Dongmei & Meadows, Maureen & Wong, Donna & Xia, Senmao, 2021. "Understanding consumers’ social media engagement behaviour: An examination of the moderation effect of social media context," Journal of Business Research, Elsevier, vol. 122(C), pages 835-846.
    2. Pavlova, Alina & Berkers, Pauwke, 2020. "Mental health discourse and social media: Which mechanisms of cultural power drive discourse on Twitter," Social Science & Medicine, Elsevier, vol. 263(C).
    3. Haijun Bao & Chengcheng Wang & Lu Han & Shaohua Wu & Liming Lou & Baogen Xu & Yanfang Liu, 2020. "Resources and Environmental Pressure, Carrying Capacity, And Governance: A Case Study of Yangtze River Economic Belt," Sustainability, MDPI, vol. 12(4), pages 1-18, February.

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