Paper: Contrasting Opposing Views of News Articles on Contentious Issues

ACL ID P11-1035
Title Contrasting Opposing Views of News Articles on Contentious Issues
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011
Authors

We present disputant relation-based meth- od for classifying news articles on conten- tious issues. We observe that the disputants of a contention are an important feature for understanding the discourse. It performs unsupervised classification on news articles based on disputant relations, and helps readers intuitively view the articles through the opponent-based frame. The readers can attain balanced understanding on the con- tention, free from a specific biased view. We applied a modified version of HITS al- gorithm and an SVM classifier trained with pseudo-relevant data for article analysis.