Paper: Recognizing Rare Social Phenomena in Conversation: Empowerment Detection in Support Group Chatrooms

ACL ID P13-1011
Title Recognizing Rare Social Phenomena in Conversation: Empowerment Detection in Support Group Chatrooms
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2013
Authors

Automated annotation of social behavior in conversation is necessary for large-scale analysis of real-world conversational data. Important behavioral categories, though, are often sparse and often appear only in specific subsections of a conversation. This makes supervised machine learning difficult, through a combination of noisy features and unbalanced class distribu- tions. We propose within-instance con- tent selection, using cue features to selec- tively suppress sections of text and bias- ing the remaining representation towards minority classes. We show the effective- ness of this technique in automated anno- tation of empowerment language in online support group chatrooms. Our technique is significantly more accurate than multi- ple baselines, especially when prioritizing high prec...