Appeal and Scope of Misinformation Spread by AI Agents and Humans
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866912364344901632 |
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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 influence of misinformation and the role of AI agents, called bots, on social network platforms. To quantify the impact of misinformation, it proposes two new metrics based on attributes of tweet engagement and user network position: Appeal, which measures the popularity of the tweet, and Scope, which measures the potential reach of the tweet. In addition, it analyzes 5.8 million misinformation tweets on the COVID-19 vaccine discourse over three time periods: Pre-Vaccine, Vaccine Launch, and Post-Vaccine. Results show that misinformation was more prevalent during the first two periods. Human-generated misinformation tweets tend to have higher appeal and scope compared to bot-generated ones. Tweedie regression analysis reveals that human-generated misinformation tweets were most concerning during Vaccine Launch week, whereas bot-generated misinformation reached its highest appeal and scope during the Pre-Vaccine period. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_04028 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Appeal and Scope of Misinformation Spread by AI Agents and Humans Ng, Lynnette Hui Xian Zhou, Wenqi Carley, Kathleen M. Social and Information Networks Physics and Society This work examines the influence of misinformation and the role of AI agents, called bots, on social network platforms. To quantify the impact of misinformation, it proposes two new metrics based on attributes of tweet engagement and user network position: Appeal, which measures the popularity of the tweet, and Scope, which measures the potential reach of the tweet. In addition, it analyzes 5.8 million misinformation tweets on the COVID-19 vaccine discourse over three time periods: Pre-Vaccine, Vaccine Launch, and Post-Vaccine. Results show that misinformation was more prevalent during the first two periods. Human-generated misinformation tweets tend to have higher appeal and scope compared to bot-generated ones. Tweedie regression analysis reveals that human-generated misinformation tweets were most concerning during Vaccine Launch week, whereas bot-generated misinformation reached its highest appeal and scope during the Pre-Vaccine period. |
| title | Appeal and Scope of Misinformation Spread by AI Agents and Humans |
| topic | Social and Information Networks Physics and Society |
| url | https://arxiv.org/abs/2505.04028 |