Exploring Cyberbullying and Other Toxic Behavior in Team Competition Online Games
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Abstract (arXiv)
In this work we explore cyberbullying and other toxic behavior in team competition online games. Using a dataset of over 10 million player reports on 1.46 million toxic players along with corresponding crowdsourced decisions, we test several hypotheses drawn from theories explaining toxic behavior. Besides providing large-scale, empirical based understanding of toxic behavior, our work can be used as a basis for building systems to detect, prevent, and counter-act toxic behavior.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Apr 2015.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 3; 2024: 1; 2025: 2; 2026: 2.
10 papers.
- 2023Can Large Language Models Transform Computational Social Science?cited by 245
- 2023Is ChatGPT better than Human Annotators? Potential and Limitations of ChatGPT in Explaining Implicit Hate Speechcited by 165
- 2021CONDA: a CONtextual Dual-Annotated dataset for in-game toxicity understanding and detectioncited by 14
- 2022Understanding Toxicity Triggers on Reddit in the Context of Singaporecited by 3
- 2024CUPID: Improving Battle Fairness and Position Satisfaction in Online MOBA Games with a Re-matchmaking Systemcited by 2
- 2023Beyond Toxic: Toxicity Detection Datasets are Not Enough for Brand Safetycited by 1
- 2025Reinforcement Learning for Efficient Toxicity Detection in Competitive Online Video Gamescited by 0
- 2025Context-Aware Toxicity Detection in Multiplayer Games: Integrating Domain-Adaptive Pretraining and Match Metadatacited by 0
- 2026"bot lane noob" Towards Deployment of NLP-based Toxicity Detectors in Video Gamescited by 0
- 2026PSK@EEUCA 2026: Fine-Tuning Large Language Models with Synthetic Data Augmentation for Multi-Class Toxicity Detection in Gaming Chatcited by 0
- 2026PSK@EEUCA 2026: Fine-Tuning Large Language Models with Synthetic Data Augmentation for Multi-Class Toxicity Detection in Gaming Chat8 May 2026
- 2026"bot lane noob" Towards Deployment of NLP-based Toxicity Detectors in Video Games11 Apr 2026
- 2025Context-Aware Toxicity Detection in Multiplayer Games: Integrating Domain-Adaptive Pretraining and Match Metadata2 Apr 2025
- 2025Reinforcement Learning for Efficient Toxicity Detection in Competitive Online Video Games26 Mar 2025
- 2024CUPID: Improving Battle Fairness and Position Satisfaction in Online MOBA Games with a Re-matchmaking System28 Jun 2024
- 2023Can Large Language Models Transform Computational Social Science?12 Apr 2023
- 2023Beyond Toxic: Toxicity Detection Datasets are Not Enough for Brand Safety27 Mar 2023
- 2023Is ChatGPT better than Human Annotators? Potential and Limitations of ChatGPT in Explaining Implicit Hate Speech11 Feb 2023
- 2022Understanding Toxicity Triggers on Reddit in the Context of Singapore19 Apr 2022
- 2021CONDA: a CONtextual Dual-Annotated dataset for in-game toxicity understanding and detection11 Jun 2021