Investigating the heterogenous effects of a massive content moderation intervention via Difference-in-Differences
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866911030873948160 |
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| author | Cima, Lorenzo Tessa, Benedetta Cresci, Stefano Trujillo, Amaury Avvenuti, Marco |
| author_facet | Cima, Lorenzo Tessa, Benedetta Cresci, Stefano Trujillo, Amaury Avvenuti, Marco |
| contents | In today's online environments, users encounter harm and abuse on a daily basis. Therefore, content moderation is crucial to ensure their safety and well-being. However, the effectiveness of many moderation interventions is still uncertain. Here, we apply a causal inference approach to shed light on the effectiveness of The Great Ban, a massive social media deplatforming intervention on Reddit. We analyze 53M comments shared by nearly 34K users, providing in-depth results on both the intended and unintended consequences of the ban. Our causal analyses reveal that 15.6% of the moderated users abandoned the platform while the remaining ones decreased their overall toxicity by 4.1%. Nonetheless, a small subset of users exhibited marked increases in both the intensity and volume of toxic behavior, particularly among those whose activity levels changed after the intervention. However, these reactions were not accompanied by greater activity or engagement, suggesting that even the most toxic users maintained a limited overall impact. Our findings bring to light new insights on the effectiveness of deplatforming moderation interventions. Furthermore, they also contribute to informing future content moderation strategies and regulations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_04037 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Investigating the heterogenous effects of a massive content moderation intervention via Difference-in-Differences Cima, Lorenzo Tessa, Benedetta Cresci, Stefano Trujillo, Amaury Avvenuti, Marco Computers and Society Human-Computer Interaction In today's online environments, users encounter harm and abuse on a daily basis. Therefore, content moderation is crucial to ensure their safety and well-being. However, the effectiveness of many moderation interventions is still uncertain. Here, we apply a causal inference approach to shed light on the effectiveness of The Great Ban, a massive social media deplatforming intervention on Reddit. We analyze 53M comments shared by nearly 34K users, providing in-depth results on both the intended and unintended consequences of the ban. Our causal analyses reveal that 15.6% of the moderated users abandoned the platform while the remaining ones decreased their overall toxicity by 4.1%. Nonetheless, a small subset of users exhibited marked increases in both the intensity and volume of toxic behavior, particularly among those whose activity levels changed after the intervention. However, these reactions were not accompanied by greater activity or engagement, suggesting that even the most toxic users maintained a limited overall impact. Our findings bring to light new insights on the effectiveness of deplatforming moderation interventions. Furthermore, they also contribute to informing future content moderation strategies and regulations. |
| title | Investigating the heterogenous effects of a massive content moderation intervention via Difference-in-Differences |
| topic | Computers and Society Human-Computer Interaction |
| url | https://arxiv.org/abs/2411.04037 |