Dynamic simulation of social media challenge participation to examine intervention strategies
Amro Khasawneh (),
Kapil Chalil Madathil,
Kevin M. Taaffe,
Heidi Zinzow,
Amal Ponathil,
Sreenath Chalil Madathil,
Siddhartha Nambiar,
Gaurav Nanda and
Patrick J. Rosopa
Additional contact information
Amro Khasawneh: Mercer University
Kapil Chalil Madathil: Clemson University
Kevin M. Taaffe: Clemson University
Heidi Zinzow: Clemson University
Amal Ponathil: Clemson University
Sreenath Chalil Madathil: Binghamton University
Siddhartha Nambiar: North Carolina State University
Gaurav Nanda: Purdue University
Patrick J. Rosopa: Clemson University
Journal of Computational Social Science, 2022, vol. 5, issue 2, No 20, 1637-1662
Abstract:
Abstract Recently, the use of social media by adolescents and young adults has significantly increased. While this new landscape of cyberspace offers young Internet users many benefits, it also exposes them to numerous risks. One such phenomenon receiving limited research attention is the advent and propagation of viral social media challenges. Several of these challenges entail self-harming behavior, which combined with their viral nature, poses physical and psychological risks for the participants and the viewers. In this paper, we show how agent-based modeling (ABM) can be used to investigate the effect of educational intervention programs to reduce participation in social media challenges at multiple levels—family, school, and community. In addition, we show how the effect of these education-based interventions can be compared to social media-based policy interventions. Our model takes into account the “word of mouth” effect of these interventions which could either decrease participation in social media challenge further than expected or unintentionally cause others to participate. We suggest that educational interventions at combined family and school levels are the most efficient type of long-term intervention, since they target the root of the problem, while social media-based policies act as a retrospective solution.
Keywords: Agent-based model; Web-based challenges; Self-injurious behavior; Behavior; Integrated behavioral model; Social media (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s42001-022-00183-7
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