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Interplay of rumor propagation and clarification on social media during crisis events - A game-theoretic approach

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  • Agarwal, Puneet
  • Aziz, Ridwan Al
  • Zhuang, Jun

Abstract

For a rapid dissemination of information during crisis events, official agencies and disaster relief organizations have been utilizing social media platforms, which are susceptible to rumor propagation. To minimize the impact of rumors with limited time and resources, the agencies and social media companies not only need to wisely choose the cases to clarify amongst the numerous cases, but they should also make an informed decision on the timing of clarification. Reacting fast can be misjudged as an obvious best policy as partial/imprecise information may fail to contain the impact of the rumors. On the other hand, investment in terms of time, effort, and money to clarify with more complete information also allows the rumors to spread with their full force during the learning phase, thereby making the process of decision-making very challenging. The objective of this paper is to determine the optimal strategies for the official agencies and social media companies by developing two novel sequential game-theoretic models, namely “Rumor Selection for Clarification” and “Learning for Rumor Clarification”, that can help decide which rumor to clarify and when to clarify, respectively. Results from this study indicate that posting verified information on social media reduces the uncertainties involved in rumor transmission, thereby enabling social media users to make informed decisions on whether to support or oppose the rumor being circulated. This verification needs to be obtained within reasonable limits of time and cost to keep the learning process worthwhile.

Suggested Citation

  • Agarwal, Puneet & Aziz, Ridwan Al & Zhuang, Jun, 2022. "Interplay of rumor propagation and clarification on social media during crisis events - A game-theoretic approach," European Journal of Operational Research, Elsevier, vol. 298(2), pages 714-733.
    • Handle: RePEc:eee:ejores:v:298:y:2022:i:2:p:714-733
    DOI: 10.1016/j.ejor.2021.06.060
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    References listed on IDEAS

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    4. Lian, Ying & Tang, Huiting & Xiang, Mengting & Dong, Xuefan, 2024. "Public attitudes and sentiments toward ChatGPT in China: A text mining analysis based on social media," Technology in Society, Elsevier, vol. 76(C).

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