The Structural Influence of Low-Credibility Narratives During the COVID-19 Vaccine Rollout
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866910279484309504 |
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| author | Ng, Lynnette Hui Xian Zhou, Wenqi Carley, Kathleen M. |
| author_facet | Ng, Lynnette Hui Xian Zhou, Wenqi Carley, Kathleen M. |
| contents | This work examines the structural influence of low-credibility narratives and the comparative role of automated accounts (bots) versus human users on social media platforms. To more accurately quantify the structural influence of a narrative on social media, this study proposes two novel metrics: (1) Appeal, which measures the network-weighted popularity of a message; and (2) Scope, which measures an author's message popularity-weighted network penetration. Applying these metrics, this study analyzes 5.8 million messages from X that contain low-credibility narratives regarding COVID-19 vaccine across three distinct temporal stages: Pre-Vaccine, Vaccine Launch, and Post-Launch. The results demonstrate that across all timeframes, human-distributed low-credibility narratives achieved higher structural influence compared to those generated by automated accounts. Furthermore, statistical analysis reveals a significant conditional temporal effect: human-driven low-credibility narratives attained their highest Appeal and Scope during the focal Vaccine Launch week, whereas automated accounts maximized their Appeal and Scope during the highly uncertain Pre-Vaccine period. These findings highlight the distinct operational capacities of automated and organic accounts, illustrating how the Appeal and Scope of low-credibility narratives is moderated by the lifecycle stages of critical public events. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2606_01630 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | The Structural Influence of Low-Credibility Narratives During the COVID-19 Vaccine Rollout Ng, Lynnette Hui Xian Zhou, Wenqi Carley, Kathleen M. Social and Information Networks This work examines the structural influence of low-credibility narratives and the comparative role of automated accounts (bots) versus human users on social media platforms. To more accurately quantify the structural influence of a narrative on social media, this study proposes two novel metrics: (1) Appeal, which measures the network-weighted popularity of a message; and (2) Scope, which measures an author's message popularity-weighted network penetration. Applying these metrics, this study analyzes 5.8 million messages from X that contain low-credibility narratives regarding COVID-19 vaccine across three distinct temporal stages: Pre-Vaccine, Vaccine Launch, and Post-Launch. The results demonstrate that across all timeframes, human-distributed low-credibility narratives achieved higher structural influence compared to those generated by automated accounts. Furthermore, statistical analysis reveals a significant conditional temporal effect: human-driven low-credibility narratives attained their highest Appeal and Scope during the focal Vaccine Launch week, whereas automated accounts maximized their Appeal and Scope during the highly uncertain Pre-Vaccine period. These findings highlight the distinct operational capacities of automated and organic accounts, illustrating how the Appeal and Scope of low-credibility narratives is moderated by the lifecycle stages of critical public events. |
| title | The Structural Influence of Low-Credibility Narratives During the COVID-19 Vaccine Rollout |
| topic | Social and Information Networks |
| url | https://arxiv.org/abs/2606.01630 |