Conference Proceeding Article
Advances in sentiment analysis have enabled extraction of user relations implied in online textual exchanges such as forum posts. However, recent studies in this direction only consider direct relation extraction from text. As user interactions can be sparse in online discussions, we propose to apply collaborative filtering through probabilistic matrix factorization to generalize and improve the opinion matrices extracted from forum posts. Experiments with two tasks show that the learned latent factor representation can give good performance on a relation polarity prediction task and improve the performance of a subgroup detection task.
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics-Human Language Technologies 2013, 9-14 June, Atlanta
City or Country
QIU, Minghui; YANG, Liu; and JIANG, Jing.
Mining User Relations from Online Discussions using Sentiment Analysis and Probabilistic Matrix Factorization. (2013). Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics-Human Language Technologies 2013, 9-14 June, Atlanta. 401-410. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1891
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.