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Digital Resilience in Dealing with Misinformation on Social Media during COVID-19

Author

Listed:
  • Stefka Schmid

    (TU Darmstadt, Science and Technology for Peace and Security (PEASEC))

  • Katrin Hartwig

    (TU Darmstadt, Science and Technology for Peace and Security (PEASEC))

  • Robert Cieslinski

    (TU Darmstadt, Science and Technology for Peace and Security (PEASEC))

  • Christian Reuter

    (TU Darmstadt, Science and Technology for Peace and Security (PEASEC))

Abstract

In crises such as the COVID-19 pandemic, it is crucial to support users when dealing with social media content. Considering digital resilience, we propose a web app based on Social Network Analysis (SNA) to provide an overview of potentially misleading vs. non-misleading content on Twitter, which can be explored by users and enable foundational learning. The latter aims at systematically identifying thematic patterns which may be associated with misleading information. Additionally, it entails reflecting on indicators of misleading tweets which are proposed to approach classification of tweets. Paying special attention to non-expert users of social media, we conducted a two-step Think Aloud study for evaluation. While participants valued the opportunity to generate new knowledge and the diversity of the application, qualities such as equality and rapidity may be further improved. However, learning effects outweighed individual costs as all users were able to shift focus onto relevant features, such as hashtags, while readily pointing out content characteristics. Our design artifact connects to learning-oriented interventions regarding the spread of misleading information and tackles information overload by a SNA-based plug-in.

Suggested Citation

  • Stefka Schmid & Katrin Hartwig & Robert Cieslinski & Christian Reuter, 2024. "Digital Resilience in Dealing with Misinformation on Social Media during COVID-19," Information Systems Frontiers, Springer, vol. 26(2), pages 477-499, April.
    • Handle: RePEc:spr:infosf:v:26:y:2024:i:2:d:10.1007_s10796-022-10347-5
    DOI: 10.1007/s10796-022-10347-5
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    References listed on IDEAS

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    1. Marc-André Kaufhold & Nicola Rupp & Christian Reuter & Matthias Habdank, 2020. "Mitigating information overload in social media during conflicts and crises: design and evaluation of a cross-platform alerting system," Behaviour and Information Technology, Taylor & Francis Journals, vol. 39(3), pages 319-342, March.
    2. Nicole M. Krause & Isabelle Freiling & Becca Beets & Dominique Brossard, 2020. "Fact-checking as risk communication: the multi-layered risk of misinformation in times of COVID-19," Journal of Risk Research, Taylor & Francis Journals, vol. 23(7-8), pages 1052-1059, August.
    3. Chengcheng Shao & Pik-Mai Hui & Lei Wang & Xinwen Jiang & Alessandro Flammini & Filippo Menczer & Giovanni Luca Ciampaglia, 2018. "Anatomy of an online misinformation network," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-23, April.
    4. Elena Milani & Emma Weitkamp & Peter Webb, 2020. "The Visual Vaccine Debate on Twitter: A Social Network Analysis," Media and Communication, Cogitatio Press, vol. 8(2), pages 364-375.
    5. Hyehyun Hong & Hyo Jung Kim, 2020. "Antecedents and Consequences of Information Overload in the COVID-19 Pandemic," IJERPH, MDPI, vol. 17(24), pages 1-15, December.
    6. Gordon Pennycook & Ziv Epstein & Mohsen Mosleh & Antonio A. Arechar & Dean Eckles & David G. Rand, 2021. "Shifting attention to accuracy can reduce misinformation online," Nature, Nature, vol. 592(7855), pages 590-595, April.
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