Paper: Mining User Relations from Online Discussions using Sentiment Analysis and Probabilistic Matrix Factorization

ACL ID N13-1041
Title Mining User Relations from Online Discussions using Sentiment Analysis and Probabilistic Matrix Factorization
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2013
Authors

Advances in sentiment analysis have enabled extraction of user relations implied in online textual exchanges such as forum posts. How- ever, recent studies in this direction only con- sider direct relation extraction from text. As user interactions can be sparse in online dis- cussions, we propose to apply collaborative filtering through probabilistic matrix factor- ization to generalize and improve the opinion matrices extracted from forum posts. Exper- iments with two tasks show that the learned latent factor representation can give good per- formance on a relation polarity prediction task and improve the performance of a subgroup detection task.