Exploring Cyberbullying and Other Toxic Behavior in Team Competition Online Games

Abstract

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.

arXiv commentCHI'15

References in corpus (3)

• Multirelational Organization of Large-scale Social Networks in an Online World
• STFU NOOB! Predicting Crowdsourced Decisions on Toxic Behavior in Online Games
• Linguistic Analysis of Toxic Behavior in an Online Video Game

Cited by in corpus (8)

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• Machine learning and semantic analysis of in-game chat for cyberbullying
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• Information Overload in Group Communication: From Conversation to Cacophony in the Twitch Chat
• Designing Toxic Content Classification for a Diversity of Perspectives
• The Art of Drafting: A Team-Oriented Hero Recommendation System for Multiplayer Online Battle Arena Games
• Achievement and Friends: Key Factors of Player Retention Vary Across Player Levels in Online Multiplayer Games
• The Proficiency-Congruency Dilemma: Virtual Team Design and Performance in Multiplayer Online Games