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Fun with Frustration? TikTok Influencers' Emotional Expression Predicts User Engagement with COVID-19 Vaccination Messages.
Yang, Ellie Fan; Kriss, Lauren A; Sun, Yibing.
Afiliação
  • Yang EF; School of Communication and Mass Media, Northwest Missouri State University.
  • Kriss LA; School of Journalism and Mass Communication, University of Wisconsin-Madison.
  • Sun Y; School of Journalism and Mass Communication, University of Wisconsin-Madison.
Health Commun ; : 1-16, 2023 Sep 27.
Article em En | MEDLINE | ID: mdl-37766504
This study examined what kinds of TikTok video and message features are associated with user engagement in the context of COVID-19 vaccination. Content analysis was applied to study a sample of 223 COVID-19 vaccination-related videos from creators with at least 10,000 followers. The content analysis involved coding themes, video formats, the valence of attitude toward vaccination, and emotional expressions from the influencers. A majority of videos showcased personal vaccination experiences, followed by fictitious dramas and instructional information. More fictitious dramas expressed unclear attitudes, neither explicitly supporting nor opposing the COVID-19 vaccine, compared to personal vaccination stories and instructional videos. Some imaginative and dramatic scenes, such as zombie transformation or dramatic spasms after taking the vaccines, were widely imitated across influencers, perhaps humorously, and raised concerns about diminishing positive images of vaccine uptake. Videos with simultaneous expression of humor and frustration significantly predicted engagement when the video content opposed or was uncertain about taking the vaccine, implying the effectiveness of mixed emotional attributes within a message. This study provides insight into how social context and message choices by creators interact to influence audience engagement.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article