Modeling topic control to detect influence in conversations using nonparametric topic models
Abstract
Identifying influential speakers in multi-party conversations has been the focus of research in communication, sociology, and psychology for decades. It has been long acknowledged qualitatively that controlling the null of a conversation is a sign of influence. To capture who introduces new topics in conversations, we introduce SITS--Speaker Identity for Topic Segmentation--a nonparametric hierarchical Bayesian model that is capable of...
Paper Details
Title
Modeling topic control to detect influence in conversations using nonparametric topic models
Published Date
Jun 1, 2014
Journal
Volume
95
Issue
3
Pages
381 - 421
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