中文简单介绍：本文对怎样基于情感分析和概率矩阵分解从网络论坛讨论中挖掘用户关系进行了深入研究。
论文出处：NAACL‘13.
英文摘要： 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.
下载链接：http://aclweb.org/anthology/N/N13/N13-1041.pdf
开源Code链接：https://github.com/yangliuy/NLPForumPostOTE
Data链接：https://github.com/yangliuy/Debate-DataSets_NAACL13
