Coping and Regulatory Responses on Social Media during Health Crisis: a Large-scale Analysis

dc.contributor.author Abramova, Olga
dc.contributor.author Batzel, Katharina
dc.contributor.author Modesti, Daniela
dc.date.accessioned 2021-12-24T17:52:26Z
dc.date.available 2021-12-24T17:52:26Z
dc.date.issued 2022-01-04
dc.description.abstract During a crisis event, social media enables two-way communication and many-to-many information broadcasting, browsing others’ posts, publishing own content, and public commenting. These records can deliver valuable insights to approach problematic situations effectively. Our study explores how social media communication can be analyzed to understand the responses to health crises better. Results based on nearly 800 K tweets indicate that the coping and regulation foci framework holds good explanatory power, with four clusters salient in public reactions: 1) “Understanding” (problem-promotion); 2) “Action planning” (problem-prevention); 3) “Hope” (emotion-promotion) and 4) “Reassurance” (emotion-prevention). Second, the inter-temporal analysis shows high volatility of topic proportions and a shift from self-centered to community-centered topics during the course of the event. The insights are beneficial for research on crisis management and practicians who are interested in large-scale monitoring of their audience for well-informed decision-making.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2022.457
dc.identifier.isbn 978-0-9981331-5-7
dc.identifier.uri http://hdl.handle.net/10125/79793
dc.language.iso eng
dc.relation.ispartof Proceedings of the 55th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Digital-Enabled Human-Information Interaction
dc.subject big data
dc.subject data mining
dc.subject health crisis
dc.subject social media
dc.title Coping and Regulatory Responses on Social Media during Health Crisis: a Large-scale Analysis
dc.type.dcmi text
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