Abstract
We tackle the problem of automatically detecting controversial issues and their subtopics from news articles. We define a controversial issue as a concept that invokes conflicting sentiments or views and a subtopic as a reason or factor that gives a particular sentiment or view to the issue. Conforming to the definitions, we propose a controversial issue detection method that considers the magnitude of sentiment information and the difference between the amounts of two different polarities. For subtopic identification, candidate phrases are generated and checked for containing five different features, some of which attempts to capture the relationship between the identified issue phrase and the candidate subtopic phrase. Through an experiment and analysis using the MPQA corpus consisting of news articles, we found that the proposed method is promising for both of the tasks although many additional research issues remain to be tapped in the future.
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MPQA corpus, http://www.cs.pitt.edu/mpqa
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Choi, Y., Jung, Y., Myaeng, SH. (2010). Identifying Controversial Issues and Their Sub-topics in News Articles. In: Chen, H., Chau, M., Li, Sh., Urs, S., Srinivasa, S., Wang, G.A. (eds) Intelligence and Security Informatics. PAISI 2010. Lecture Notes in Computer Science, vol 6122. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13601-6_16
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DOI: https://doi.org/10.1007/978-3-642-13601-6_16
Publisher Name: Springer, Berlin, Heidelberg
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