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http://dx.doi.org/10.15207/JKCS.2020.11.5.199

An Analysis of the 2017 Korean Presidential Election Using Text Mining  

An, Eunhee (School of Business, Yonsei University)
An, Jungkook (Department of Business Administration, Sun Moon University)
Publication Information
Journal of the Korea Convergence Society / v.11, no.5, 2020 , pp. 199-207 More about this Journal
Abstract
Recently, big data analysis has drawn attention in various fields as it can generate value from large amounts of data and is also used to run political campaigns or predict results. However, existing research had limitations in compiling information about candidates at a high-level by analyzing only specific SNS data. Therefore, this study analyses news trends, topics extraction, sentiment analysis, keyword analysis, comment analysis for the 2017 presidential election of South Korea. The results show that various topics had been generated, and online opinions are extracted for trending keywords of respective candidates. This study also shows that portal news and comments can serve as useful tools for predicting the public's opinion on social issues. This study will This paper advances a building strategic course of action by providing a method of analyzing public opinion across various fields.
Keywords
Presidential election; Text mining; Topic extraction; Sentiment analysis; Comment analysis;
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Times Cited By KSCI : 10  (Citation Analysis)
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