Conversations Gone Awry: Detecting Early Signs of Conversational Failure
Justine Zhang | Jonathan Chang | Cristian Danescu-Niculescu-Mizil | Lucas Dixon | Yiqing Hua | Dario Taraborelli | Nithum Thain
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
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.
Not-So-Latent Dirichlet Allocation: Collapsed Gibbs Sampling Using Human Judgments
Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon’s Mechanical Turk
PU-BCD: Exponential Family Models for the Coarse- and Fine-Grained All-Words Tasks
Jonathan Chang | Miroslav Dudík | David Blei
Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007)
- Justine Zhang 1
- Cristian Danescu-Niculescu-Mizil 1
- Lucas Dixon 1
- Yiqing Hua 1
- Dario Taraborelli 1
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