What You Say and How You Say it: Joint Modeling of Topics and Discourse in Microblog Conversations
Published
2019-06-04
Jichuan Zeng
,
Jing Li
,
Yulan He
,
Cuiyun Gao
,
Michael Lyu
,
Irwin King
Jichuan Zeng
The Chinese University of Hong Kong
Jing Li
Tencent AI Lab
Yulan He
The University of Warwick
Cuiyun Gao
The Chinese University of Hong Kong
Michael Lyu
The Chinese University of Hong Kong
Irwin King
The Chinese University of Hong Kong
Abstract
This paper presents an unsupervised framework for jointly modeling topic content and discourse behavior in microblog conversations. Concretely, we propose a neural model to discover word clusters indicating what a conversation concerns (i.e., topics) and those reflecting how participants voice their opinions (i.e., discourse). Extensive experiments show that our model can yield both coherent topics and meaningful discourse behavior. Further study shows that our topic and discourse representations can benefit the classification of microblog messages, especially when they are jointly trained with the classifier.
Article at MIT Press
(presented at ACL 2019)