Anyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions
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Abstract (arXiv)
In online communities, antisocial behavior such as trolling disrupts constructive discussion. While prior work suggests that trolling behavior is confined to a vocal and antisocial minority, we demonstrate that ordinary people can engage in such behavior as well. We propose two primary trigger mechanisms: the individual's mood, and the surrounding context of a discussion (e.g., exposure to prior trolling behavior). Through an experiment simulating an online discussion, we find that both negative mood and seeing troll posts by others significantly increases the probability of a user trolling, and together double this probability. To support and extend these results, we study how these same mechanisms play out in the wild via a data-driven, longitudinal analysis of a large online news discussion community. This analysis reveals temporal mood effects, and explores long range patterns of repeated exposure to trolling. A predictive model of trolling behavior shows that mood and discussion context together can explain trolling behavior better than an individual's history of trolling. These results combine to suggest that ordinary people can, under the right circumstances, behave like trolls.
Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Feb 2017.
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Citing papers per year: 2021: 7; 2022: 5; 2023: 4; 2024: 3; 2025: 6; 2026: 5.
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- 2023Reinforcement Learning-based Counter-Misinformation Response Generation: A Case Study of COVID-19 Vaccine Misinformation11 Mar 2023
- 2023Characterizing the Entities in Harmful Memes: Who is the Hero, the Villain, the Victim?26 Jan 2023
- 2023Critical Perspectives: A Benchmark Revealing Pitfalls in PerspectiveAPI5 Jan 2023
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- 2022Spillover of Antisocial Behavior from Fringe Platforms: The Unintended Consequences of Community Banning20 Sep 2022
- 2022A Context-Sensitive Word Embedding Approach for The Detection of Troll Tweets17 Jul 2022
- 2022DISARM: Detecting the Victims Targeted by Harmful Memes11 May 2022
- 2022Effect of Toxic Review Content on Overall Product Sentiment8 Jan 2022
- 2021Countering Online Hate Speech: An NLP Perspective7 Sep 2021
- 2021Measuring and Improving Model-Moderator Collaboration using Uncertainty Estimation9 Jul 2021
- 2021AOMD: An Analogy-aware Approach to Offensive Meme Detection on Social Media21 Jun 2021
- 2021Interpretable Multi-Modal Hate Speech Detection2 Mar 2021
- 2021Conversations Gone Alright: Quantifying and Predicting Prosocial Outcomes in Online Conversations16 Feb 2021
- 2021Characterizing Student Engagement Moods for Dropout Prediction in Question Pool Websites31 Jan 2021
- 2021I Beg to Differ: A study of constructive disagreement in online conversations26 Jan 2021
- 2023Can Large Language Models Transform Computational Social Science?cited by 245
- 2023Reinforcement Learning-based Counter-Misinformation Response Generation: A Case Study of COVID-19 Vaccine Misinformationcited by 39
- 2021Conversations Gone Alright: Quantifying and Predicting Prosocial Outcomes in Online Conversationscited by 20
- 2022DISARM: Detecting the Victims Targeted by Harmful Memescited by 20
- 2021I Beg to Differ: A study of constructive disagreement in online conversationscited by 18
- 2021Measuring and Improving Model-Moderator Collaboration using Uncertainty Estimationcited by 18
- 2022Spillover of Antisocial Behavior from Fringe Platforms: The Unintended Consequences of Community Banningcited by 14
- 2023Characterizing the Entities in Harmful Memes: Who is the Hero, the Villain, the Victim?cited by 14
- 2021AOMD: An Analogy-aware Approach to Offensive Meme Detection on Social Mediacited by 13
- 2021Countering Online Hate Speech: An NLP Perspectivecited by 12
- 2022Thread With Caution: Proactively Helping Users Assess and Deescalate Tension in Their Online Discussionscited by 11
- 2021Interpretable Multi-Modal Hate Speech Detectioncited by 10
12 most cited of 27 All 27 (JSON)
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- 2026Benchmarking Multi-Modal Graph-based Social Media Popularity Prediction25 Jun 2026
- 2025Addressing Antisocial Behavior in Multi-Party Dialogs Through Multimodal Representation Learning20 Oct 2025
- 2025Queuing for Civility: Regulating Emotions and Reducing Toxicity in Digital Discourse31 Aug 2025
- 2025Before the Outrage: Challenges and Advances in Predicting Online Antisocial Behavior28 Jul 2025
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- 2025Unified Game Moderation: Soft-Prompting and LLM-Assisted Label Transfer for Resource-Efficient Toxicity Detection1 Jun 2025
- 2025Emotional Analysis of Fashion Trends Using Social Media and AI: Sentiment Analysis on Twitter for Fashion Trend Forecasting30 Apr 2025
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- 2024The Constant in HATE: Analyzing Toxicity in Reddit across Topics and Languages29 Apr 2024
- 2023Can Large Language Models Transform Computational Social Science?12 Apr 2023
12 newest of 27 All 27 (JSON)