Community Moderation and the New Epistemology of Fact Checking on Social Media
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arXiv
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| Autori principali: | , , , , , , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| author | Augenstein, Isabelle Bakker, Michiel Chakraborty, Tanmoy Corney, David Ferrara, Emilio Gurevych, Iryna Hale, Scott Hovy, Eduard Ji, Heng Larraz, Irene Menczer, Filippo Nakov, Preslav Papotti, Paolo Sahnan, Dhruv Warren, Greta Zagni, Giovanni |
| author_facet | Augenstein, Isabelle Bakker, Michiel Chakraborty, Tanmoy Corney, David Ferrara, Emilio Gurevych, Iryna Hale, Scott Hovy, Eduard Ji, Heng Larraz, Irene Menczer, Filippo Nakov, Preslav Papotti, Paolo Sahnan, Dhruv Warren, Greta Zagni, Giovanni |
| contents | Social media platforms have traditionally relied on internal moderation teams and partnerships with independent fact-checking organizations to identify and flag misleading content. Recently, however, platforms including X (formerly Twitter) and Meta have shifted towards community-driven content moderation by launching their own versions of crowd-sourced fact-checking -- Community Notes. If effectively scaled and governed, such crowd-checking initiatives have the potential to combat misinformation with increased scale and speed as successfully as community-driven efforts once did with spam. Nevertheless, general content moderation, especially for misinformation, is inherently more complex. Public perceptions of truth are often shaped by personal biases, political leanings, and cultural contexts, complicating consensus on what constitutes misleading content. This suggests that community efforts, while valuable, cannot replace the indispensable role of professional fact-checkers. Here we systemically examine the current approaches to misinformation detection across major platforms, explore the emerging role of community-driven moderation, and critically evaluate both the promises and challenges of crowd-checking at scale. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_20067 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Community Moderation and the New Epistemology of Fact Checking on Social Media Augenstein, Isabelle Bakker, Michiel Chakraborty, Tanmoy Corney, David Ferrara, Emilio Gurevych, Iryna Hale, Scott Hovy, Eduard Ji, Heng Larraz, Irene Menczer, Filippo Nakov, Preslav Papotti, Paolo Sahnan, Dhruv Warren, Greta Zagni, Giovanni Social and Information Networks Artificial Intelligence Computers and Society Social media platforms have traditionally relied on internal moderation teams and partnerships with independent fact-checking organizations to identify and flag misleading content. Recently, however, platforms including X (formerly Twitter) and Meta have shifted towards community-driven content moderation by launching their own versions of crowd-sourced fact-checking -- Community Notes. If effectively scaled and governed, such crowd-checking initiatives have the potential to combat misinformation with increased scale and speed as successfully as community-driven efforts once did with spam. Nevertheless, general content moderation, especially for misinformation, is inherently more complex. Public perceptions of truth are often shaped by personal biases, political leanings, and cultural contexts, complicating consensus on what constitutes misleading content. This suggests that community efforts, while valuable, cannot replace the indispensable role of professional fact-checkers. Here we systemically examine the current approaches to misinformation detection across major platforms, explore the emerging role of community-driven moderation, and critically evaluate both the promises and challenges of crowd-checking at scale. |
| title | Community Moderation and the New Epistemology of Fact Checking on Social Media |
| topic | Social and Information Networks Artificial Intelligence Computers and Society |
| url | https://arxiv.org/abs/2505.20067 |