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http://dx.doi.org/10.3743/KOSIM.2022.39.1.257

Analyzing Topic Trends and the Relationship between Changes in Public Opinion and Stock Price based on Sentiment of Discourse in Different Industry Fields using Comments of Naver News  

Oh, Chanhee (성균관대학교 문헌정보학과)
Kim, Kyuli (성균관대학교 문헌정보학과)
Zhu, Yongjun (연세대학교 문헌정보학과)
Publication Information
Journal of the Korean Society for information Management / v.39, no.1, 2022 , pp. 257-280 More about this Journal
Abstract
In this study, we analyzed comments on news articles of representative companies of the three industries (i.e., semiconductor, secondary battery, and bio industries) that had been listed as national strategic technology projects of South Korea to identify public opinions towards them. In addition, we analyzed the relationship between changes in public opinion and stock price. 'Samsung Electronics' and 'SK Hynix' in the semiconductor industry, 'Samsung SDI' and 'LG Chem' in the secondary battery industry, and 'Samsung Biologics' and 'Celltrion' in the bio-industry were selected as the representative companies and 47,452 comments of news articles about the companies that had been published from January 1, 2020, to December 31, 2020, were collected from Naver News. The comments were grouped into positive, neutral, and negative emotions, and the dynamic topics of comments over time in each group were analyzed to identify the trends of public opinion in each industry. As a result, in the case of the semiconductor industry, investment, COVID-19 related issues, trust in large companies such as Samsung Electronics, and mention of the damage caused by changes in government policy were the topics. In the case of secondary battery industries, references to investment, battery, and corporate issues were the topics. In the case of bio-industries, references to investment, COVID-19 related issues, and corporate issues were the topics. Next, to understand whether the sentiment of the comments is related to the actual stock price, for each company, the changes in the stock price and the sentiment values of the comments were compared and analyzed using visual analytics. As a result, we found a clear relationship between the changes in the sentiment value of public opinion and the stock price through the similar patterns shown in the change graphs. This study analyzed comments on news articles that are highly related to stock price, identified changes in public opinion trends in the COVID-19 era, and provided objective feedback to government agencies' policymaking.
Keywords
comments; discourse analysis; dynamic topic modeling; sentimental analysis; SNS; stock; trend analysis; visual analysis;
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