Literature DB >> 26879407

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

Christopher A Bail1.   

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.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Advocacy groups; Computational social science; Content analysis; Discursive framing; Evolutionary theory; Health communication; Social media

Mesh:

Year:  2016        PMID: 26879407     DOI: 10.1016/j.socscimed.2016.01.049

Source DB:  PubMed          Journal:  Soc Sci Med        ISSN: 0277-9536            Impact factor:   4.634


  3 in total

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Journal:  Int J Gen Med       Date:  2020-09-17

2.  Characterizing News Report of the Substandard Vaccine Case of Changchun Changsheng in China: A Text Mining Approach.

Authors:  Ping Zhou; Yao He; Chao Lyu; Xiaoguang Yang
Journal:  Vaccines (Basel)       Date:  2020-11-17

3.  When Lone Wolf Defectors Undermine the Power of the Opt-Out Default.

Authors:  Eamonn Ferguson; Ruslan Shichman; Jonathan H W Tan
Journal:  Sci Rep       Date:  2020-06-02       Impact factor: 4.996

  3 in total

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