PMF Model for Mining User Relations
Publication Type
Data Set
Year
2013
School/Department
School of Information Systems
Description/Abstract
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.
This package implements the construction of opinion matrices which are the input of PMF model. The main features include aspect identification, opinion expression identification and opinion relation extraction based on dependency path rules. More details of our methods for aspect identification, opinion identification and opinion relation extraction are described in the related paper http://aclweb.org/anthology/N13-1041.
Disciplines
Computer Sciences
Citation
Qiu, M., Yang, L., & Jiang, J. (2013). Mining User Relations from Online Discussions using Sentiment Analysis and Probabilistic Matrix Factorization. NAACL HLT 2013, 401-410. http://aclweb.org/anthology/N13-1041
Copyright
Copyright (C) 2013 by SMU Text Mining Group/Singapore Management University/Peking University
Additionally, please cite this data package
Qiu, M., Yang, L., & Jiang, J. (2013). PMF Model for Mining User Relations. Available at Github (https://github.com/yangliuy/NLPForumPostOTE) and InK Repository at Singapore Management University.