Bans vs. Warning Labels: Examining Bystanders' Support for Community-wide Moderation Interventions
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arXiv
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| Format: | Preprint |
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2023
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| _version_ | 1866909308124397568 |
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| author | Jhaver, Shagun |
| author_facet | Jhaver, Shagun |
| contents | Social media platforms like Facebook and Reddit host thousands of user-governed online communities. These platforms sanction communities that frequently violate platform policies; however, public perceptions of such sanctions remain unclear. In a pre-registered survey conducted in the US, I explore bystander perceptions of content moderation for communities that frequently feature hate speech, violent content, and sexually explicit content. Two community-wide moderation interventions are tested: (1) community bans, where all community posts are removed, and (2) community warning labels, where an interstitial warning label precedes access. I examine how third-person effects and support for free speech influence user approval of these interventions on any platform. My regression analyses show that presumed effects on others are a significant predictor of backing for both interventions, while free speech beliefs significantly influence participants' inclination for using warning labels. Analyzing the open-ended responses, I find that community-wide bans are often perceived as too coarse, and users instead value sanctions in proportion to the severity and type of infractions. I report on concerns that norm-violating communities could reinforce inappropriate behaviors and show how users' choice of sanctions is influenced by their perceived effectiveness. I discuss the implications of these results for HCI research on online harms and content moderation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2307_11880 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Bans vs. Warning Labels: Examining Bystanders' Support for Community-wide Moderation Interventions Jhaver, Shagun Human-Computer Interaction Social media platforms like Facebook and Reddit host thousands of user-governed online communities. These platforms sanction communities that frequently violate platform policies; however, public perceptions of such sanctions remain unclear. In a pre-registered survey conducted in the US, I explore bystander perceptions of content moderation for communities that frequently feature hate speech, violent content, and sexually explicit content. Two community-wide moderation interventions are tested: (1) community bans, where all community posts are removed, and (2) community warning labels, where an interstitial warning label precedes access. I examine how third-person effects and support for free speech influence user approval of these interventions on any platform. My regression analyses show that presumed effects on others are a significant predictor of backing for both interventions, while free speech beliefs significantly influence participants' inclination for using warning labels. Analyzing the open-ended responses, I find that community-wide bans are often perceived as too coarse, and users instead value sanctions in proportion to the severity and type of infractions. I report on concerns that norm-violating communities could reinforce inappropriate behaviors and show how users' choice of sanctions is influenced by their perceived effectiveness. I discuss the implications of these results for HCI research on online harms and content moderation. |
| title | Bans vs. Warning Labels: Examining Bystanders' Support for Community-wide Moderation Interventions |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2307.11880 |