Let Community Rules Be Reflected in Online Content Moderation
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Abstract (arXiv)
Content moderation is a widely used strategy to prevent the dissemination of irregular information on social media platforms. Despite extensive research on developing automated models to support decision-making in content moderation, there remains a notable scarcity of studies that integrate the rules of online communities into content moderation. This study addresses this gap by proposing a community rule-based content moderation framework that directly integrates community rules into the moderation of user-generated content. Our experiment results with datasets collected from two domains demonstrate the superior performance of models based on the framework to baseline models across all evaluation metrics. In particular, incorporating community rules substantially enhances model performance in content moderation. The findings of this research have significant research and practical implications for improving the effectiveness and generalizability of content moderation models in online communities.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 2 of its 3 references that are in the map. First posted on arXiv 21 Aug 2024.
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Citing papers per year: 2024: 6; 2025: 2; 2026: 1.
9 papers.
- 2024Comprehensive Evaluation of Multimodal AI Models in Medical Imaging Diagnosis: From Data Augmentation to Preference-Based Comparisoncited by 10
- 2024Comprehensive Overview of Artificial Intelligence Applications in Modern Industriescited by 6
- 2024DyConfidMatch: Dynamic Thresholding and Re-sampling for 3D Semi-supervised Learningcited by 1
- 2025ChromouVQA: Benchmarking Vision-Language Models under Chromatic Camouflaged Imagescited by 1
- 2026MedRAGChecker: Claim-Level Verification for Biomedical Retrieval-Augmented Generationcited by 1
- 2024Pre-trained Graphformer-based Ranking at Web-scale Search (Extended Abstract)cited by 0
- 2024Generative Pre-trained Ranking Model with Over-parameterization at Web-Scale (Extended Abstract)cited by 0
- 2024CROPS: A Deployable Crop Management System Over All Possible State Availabilitiescited by 0
- 2025Asking For It: Question-Answering for Predicting Rule Infractions in Online Content Moderationcited by 0
- 2026MedRAGChecker: Claim-Level Verification for Biomedical Retrieval-Augmented Generation10 Jan 2026
- 2025ChromouVQA: Benchmarking Vision-Language Models under Chromatic Camouflaged Images30 Nov 2025
- 2025Asking For It: Question-Answering for Predicting Rule Infractions in Online Content Moderation7 Oct 2025
- 2024Comprehensive Evaluation of Multimodal AI Models in Medical Imaging Diagnosis: From Data Augmentation to Preference-Based Comparison7 Dec 2024
- 2024DyConfidMatch: Dynamic Thresholding and Re-sampling for 3D Semi-supervised Learning13 Nov 2024
- 2024CROPS: A Deployable Crop Management System Over All Possible State Availabilities9 Nov 2024
- 2024Generative Pre-trained Ranking Model with Over-parameterization at Web-Scale (Extended Abstract)25 Sep 2024
- 2024Pre-trained Graphformer-based Ranking at Web-scale Search (Extended Abstract)25 Sep 2024
- 2024Comprehensive Overview of Artificial Intelligence Applications in Modern Industries19 Sep 2024