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http://dx.doi.org/10.7465/jkdi.2015.26.5.1167

Study on the social issue sentiment classification using text mining  

Kang, Sun-A (Department of MIS, Chungbuk National University)
Kim, Yoo Sin (Department of MIS, Chungbuk National University)
Choi, Sang Hyun (Department of MIS, Chungbuk National University)
Publication Information
Journal of the Korean Data and Information Science Society / v.26, no.5, 2015 , pp. 1167-1173 More about this Journal
Abstract
The development of information and communication technology like SNS, blogs, and bulletin boards, was provided a variety of places where you can express your thoughts and comments and allowing Big Data to grow, many people reveal the opinion of the social issues in SNS such as Twitter. In this study, we would like to pre-built sentimental dictionary about social issues and conduct a sentimental analysis with structured dictionary, to gather opinions on social issues that are created on twitter. The data that I used is "bikini", "nakkomsu" including tweet. As the result of analysis, precision is 61% and F1- score is 74%. This study expect to suggest the standard of dictionary construction allowing you to classify positive/negative opinion on specific social issues.
Keywords
Opinion mining; sentimental analysis; sentimental dictionary; social issue; text mining;
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Times Cited By KSCI : 7  (Citation Analysis)
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