Disputant Relation-Based Classification for Contrasting Opposing Views of Contentious News Issues

作者：Park Souneil^*; Kim Jungil; Lee Kyung Soon; Song Junehwa

来源：IEEE Transactions on Knowledge and Data Engineering, 2013, 25(12): 2740-2751.

DOI：10.1109/TKDE.2012.238

• Human information processing
• clustering
• classification
• and association rules
• text mining
• information browsers
• document analysis
• libraries/information repositories/publishing

Contentious news issues, such as the health care reform debate, draw much interest from the public; however, it is not simple for an ordinary user to search and contrast the opposing arguments and have a comprehensive understanding of the issues. Providing a classified view of the opposing views of the issues can help readers easily understand the issue from multiple perspectives. We present a disputant relation-based method for classifying news articles on contentious 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 and attain balanced understanding, free from a specific biased viewpoint. The method is performed in three stages: disputant extraction, disputant partitioning, and article classification. We apply a modified version of HITS algorithm and an SVM classifier trained with pseudorelevant data for article analysis. We conduct an accuracy analysis and an upper-bound analysis for the evaluation of the method.

• 出版日期2013-12