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http://dx.doi.org/10.4275/KSLIS.2019.53.4.285

Text Mining Driven Content Analysis of Social Perception on Schizophrenia Before and After the Revision of the Terminology  

Kim, Hyunji (연세대학교 문헌정보학과)
Park, Seojeong (연세대학교 문헌정보학과)
Song, Chaemin (연세대학교 문헌정보학과)
Song, Min (연세대학교 문헌정보학과)
Publication Information
Journal of the Korean Society for Library and Information Science / v.53, no.4, 2019 , pp. 285-307 More about this Journal
Abstract
In 2011, the Korean Medical Association revised the name of schizophrenia to remove the social stigma for the sick. Although it has been about nine years since the revision of the terminology, no studies have quantitatively analyzed how much social awareness has changed. Thus, this study investigates the changes in social awareness of schizophrenia caused by the revision of the disease name by analyzing Naver news articles related to the disease. For text analysis, LDA topic modeling, TF-IDF, word co-occurrence, and sentiment analysis techniques were used. The results showed that social awareness of the disease was more negative after the revision of the terminology. In addition, social awareness of the former term among two terms used after the revision was more negative. In other words, the revision of the disease did not resolve the stigma.
Keywords
Schizophrenia; Text Mining; Topic Modeling; TF-IDF; Word Co-Occurrence; Sentiment Analysis;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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