Conversations Gone Awry: Detecting Early Signs of Conversational Failure
arXiv:1805.05345
Abstract
One of the main challenges online social systems face is the prevalence of antisocial behavior, such as harassment and personal attacks. In this work, we introduce the task of predicting from the very start of a conversation whether it will get out of hand. As opposed to detecting undesirable behavior after the fact, this task aims to enable early, actionable prediction at a time when the conversation might still be salvaged. To this end, we develop a framework for capturing pragmatic devices---such as politeness strategies and rhetorical prompts---used to start a conversation, and analyze their relation to its future trajectory. Applying this framework in a controlled setting, we demonstrate the feasibility of detecting early warning signs of antisocial behavior in online discussions.
arXiv commentTo appear in the Proceedings of ACL 2018, 15 pages, 1 figure. Data, quiz, code and additional information at http://www.cs.cornell.edu/~cristian/Conversations_gone_awry.html
References in corpus (6)
- Anyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions
- Automated Hate Speech Detection and the Problem of Offensive Language
- A Computational Approach to Politeness with Application to Social Factors
- Exploring Cyberbullying and Other Toxic Behavior in Team Competition Online Games
- Measuring #GamerGate: A Tale of Hate, Sexism, and Bullying
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