TAILIEUCHUNG - Báo cáo khoa học: "Contrasting Opposing Views of News Articles on Contentious Issues"

We present 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. | Contrasting Opposing Views of News Articles on Contentious Issues Souneil Park1 KyungSoon Lee2 Junehwa Song1 2Chonbuk National University 664-14 1ga Deokjin-dong Jeonju Jeonbuk Republic of Korea selfsolee@ 1Korea Advanced Institute of Science and Technology 291 Daehak-ro Yuseong-gu Daejeon Republic of Korea spark junesong @ Abstract We present 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. The readers can attain balanced understanding on the contention free from a specific biased view. We applied a modified version of HITS algorithm and an SVM classifier trained with pseudo-relevant data for article analysis. 1 Introduction The coverage of contentious issues of a community is an essential function of journalism. Contentious issues continuously arise in various domains such as politics economy environment each issue involves diverse participants and their different complex arguments. However news articles are frequently biased and fail to fairly deliver conflicting arguments of the issue. It is difficult for ordinary readers to analyze the conflicting arguments and understand the contention they mostly perceive the issue passively often through a single article. Advanced news delivery models are required to increase awareness on conflicting views. In this paper we present disputant relationbased method for classifying news articles on con- 340 tentious issues. We observe that the disputants of a contention . people who take a position and participate in the contention such as politicians companies stakeholders civic groups experts commentators etc. are an important feature for understanding the discourse. News producers .

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