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.

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