mlsanityData to 7 Oct 2026

Something's Brewing! Early Prediction of Controversy-causing Posts from Discussion Features

arXiv 1904.07372 ↗First posted 15 Apr 2019cs.CL cs.SI physics.soc-phcited by 21

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Abstract (arXiv)

Controversial posts are those that split the preferences of a community, receiving both significant positive and significant negative feedback. Our inclusion of the word "community" here is deliberate: what is controversial to some audiences may not be so to others. Using data from several different communities on reddit.com, we predict the ultimate controversiality of posts, leveraging features drawn from both the textual content and the tree structure of the early comments that initiate the discussion. We find that even when only a handful of comments are available, e.g., the first 5 comments made within 15 minutes of the original post, discussion features often add predictive capacity to strong content-and-rate only baselines. Additional experiments on domain transfer suggest that conversation-structure features often generalize to other communities better than conversation-content features do.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Apr 2019.

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Citing papers per year: 2021: 7; 2022: 5; 2023: 2; 2024: 4; 2025: 2; 2026: 1.

21 papers.

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  1. 2022State-of-the-art generalisation research in NLP: A taxonomy and reviewcited by 97
  2. 2021Anticipating Safety Issues in E2E Conversational AI: Framework and Toolingcited by 77
  3. 2021Abuse is Contextual, What about NLP? The Role of Context in Abusive Language Annotation and Detectioncited by 19
  4. 2021Detecting Community Sensitive Norm Violations in Online Conversationscited by 18
  5. 2022Graph Learning for Anomaly Analytics: Algorithms, Applications, and Challengescited by 15
  6. 2021Countering Online Hate Speech: An NLP Perspectivecited by 12
  7. 2024DebateQA: Evaluating Question Answering on Debatable Knowledgecited by 12
  8. 2023DELPHI: Data for Evaluating LLMs' Performance in Handling Controversial Issuescited by 11
  9. 2025Evaluation and Facilitation of Online Discussions in the LLM Era: A Surveycited by 8
  10. 2021Detecting Inappropriate Messages on Sensitive Topics that Could Harm a Company's Reputationcited by 6
  11. 2024How Did We Get Here? Summarizing Conversation Dynamicscited by 6
  12. 2021Linguistic Characterization of Divisive Topics Online: Case Studies on Contentiousness in Abortion, Climate Change, and Gun Controlcited by 4
9 more
  1. 2022Anger Breeds Controversy: Analyzing Controversy and Emotions on Redditcited by 3
  2. 2023Conversation Modeling to Predict Derailmentcited by 2
  3. 2024The Constant in HATE: Analyzing Toxicity in Reddit across Topics and Languagescited by 2
  4. 2025Conversations Gone Awry, But Then? Evaluating Conversational Forecasting Modelscited by 2
  5. 2021Controversy Detection: a Text and Graph Neural Network Based Approachcited by 1
  6. 2022Beyond Plain Toxic: Detection of Inappropriate Statements on Flammable Topics for the Russian Languagecited by 1
  7. 2022Personalized Prediction of Offensive News Comments by Considering the Characteristics of Commenterscited by 0
  8. 2024Causal Effects of Trigger Words in Social Media Discussions: A Large-Scale Case Study about UK Politics on Redditcited by 0
  9. 2026From Static Analysis to Audience Dissemination: A Training-Free Multimodal Controversy Detection Multi-Agent Frameworkcited by 0