mlsanityData to 14 Oct 2026

The Gray Area: Characterizing Moderator Disagreement on Reddit

arXiv 2601.01620 ↗First posted 4 Jan 2026cs.CY cs.CL cs.ITcited by 3

Not on the map. Why?

Abstract (arXiv)

Volunteer moderators play a crucial role in sustaining online dialogue, but they often disagree about what should or should not be allowed. In this paper, we study the complexity of content moderation with a focus on disagreements between moderators, which we term the ``gray area'' of moderation. Leveraging 5 years and 4.3 million moderation log entries from 24 subreddits of different topics and sizes, we characterize how gray area, or disputed cases, differ from undisputed cases. We show that one-in-seven moderation cases are disputed among moderators, often addressing transgressions where users' intent is not directly legible, such as in trolling and brigading, as well as tensions around community governance. This is concerning, as almost half of all gray area cases involved automated moderation decisions. Through information-theoretic evaluations, we demonstrate that gray area cases are inherently harder to adjudicate than undisputed cases and show that state-of-the-art language models struggle to adjudicate them. We highlight the key role of expert human moderators in overseeing the moderation process and provide insights about the challenges of current moderation processes and tools.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 16 of its 68 references that are in the map. First posted on arXiv 4 Jan 2026.

Builds on

16 of 68 references.

References · 16

  1. 2018Representation Learning with Contrastive Predictive Codingcited by 7,777
  2. 2018Datasheets for Datasetscited by 1,386
  3. 2022BERTopic: Neural topic modeling with a class-based TF-IDF procedurecited by 801
  4. 2021Understanding Dataset Difficulty with V-Usable Informationcited by 291
  5. 2020A Theory of Usable Information Under Computational Constraintscited by 162
  6. 2021Toward a Perspectivist Turn in Ground Truthing for Predictive Computingcited by 130
  7. 2023People Make Better Edits: Measuring the Efficacy of LLM-Generated Counterfactually Augmented Data for Harmful Language Detectioncited by 25
  8. 2022Birdwatch: Crowd Wisdom and Bridging Algorithms can Inform Understanding and Reduce the Spread of Misinformationcited by 21
  9. 2021Detecting Community Sensitive Norm Violations in Online Conversationscited by 18
  10. 2025MoMoE: Mixture of Moderation Experts Framework for AI-Assisted Online Governancecited by 13
  11. 2024"Community Guidelines Make this the Best Party on the Internet": An In-Depth Study of Online Platforms' Content Moderation Policiescited by 11
  12. 2021Making Online Communities 'Better': A Taxonomy of Community Values on Redditcited by 10
4 more
  1. 2023CPL-NoViD: Context-Aware Prompt-based Learning for Norm Violation Detection in Online Communitiescited by 7
  2. 2024Venire: A Machine Learning-Guided Panel Review System for Community Content Moderationcited by 7
  3. 2023AppealMod: Inducing Friction to Reduce Moderator Workload of Handling User Appealscited by 2
  4. 2024Characterizing Political Campaigning with Lexical Mutants on Indian Social Mediacited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.