More Than Just Warnings:Exploring the Ways of Communicating Credibility Assessment on Social Media
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866929758440259584 |
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| author | Tang, Huiyun Rohles, Björn Chuai, Yuwei Lenzini, Gabriele Sergeeva, Anastasia |
| author_facet | Tang, Huiyun Rohles, Björn Chuai, Yuwei Lenzini, Gabriele Sergeeva, Anastasia |
| contents | Reducing the spread of misinformation is challenging. AI-based fact verification systems offer a promising solution by addressing the high costs and slow pace of traditional fact-checking. However, the problem of how to effectively communicate the results to users remains unsolved. Warning labels may seem an easy solution, but they fail to account for fuzzy misinformation that is not entirely fake. Additionally, users' limited attention spans and social media information should be taken into account while designing the presentation. The online experiment (n = 537) investigates the impact of sources and granularity on users' perception of information veracity and the system's usefulness and trustworthiness. Findings show that fine-grained indicators enhance nuanced opinions, information awareness, and the intention to use fact-checking systems. Source differences had minimal impact on opinions and perceptions, except for informativeness. Qualitative findings suggest the proposed indicators promote critical thinking. We discuss implications for designing concise, user-friendly AI fact-checking feedback. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_10445 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | More Than Just Warnings:Exploring the Ways of Communicating Credibility Assessment on Social Media Tang, Huiyun Rohles, Björn Chuai, Yuwei Lenzini, Gabriele Sergeeva, Anastasia Human-Computer Interaction Reducing the spread of misinformation is challenging. AI-based fact verification systems offer a promising solution by addressing the high costs and slow pace of traditional fact-checking. However, the problem of how to effectively communicate the results to users remains unsolved. Warning labels may seem an easy solution, but they fail to account for fuzzy misinformation that is not entirely fake. Additionally, users' limited attention spans and social media information should be taken into account while designing the presentation. The online experiment (n = 537) investigates the impact of sources and granularity on users' perception of information veracity and the system's usefulness and trustworthiness. Findings show that fine-grained indicators enhance nuanced opinions, information awareness, and the intention to use fact-checking systems. Source differences had minimal impact on opinions and perceptions, except for informativeness. Qualitative findings suggest the proposed indicators promote critical thinking. We discuss implications for designing concise, user-friendly AI fact-checking feedback. |
| title | More Than Just Warnings:Exploring the Ways of Communicating Credibility Assessment on Social Media |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2503.10445 |