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http://dx.doi.org/10.3743/KOSIM.2019.36.4.207

An Analysis of the Discourse Topics of Users who Exhibit Symptoms of Depression on Social Media  

Seo, Harim (연세대학교 문헌정보학과)
Song, Min (연세대학교 문헌정보학과)
Publication Information
Journal of the Korean Society for information Management / v.36, no.4, 2019 , pp. 207-226 More about this Journal
Abstract
Depression is a serious psychological disease that is expected to afflict an increasing number of people. And studies on depression have been conducted in the context of social media because social media is a platform through which users often frankly express their emotions and often reveal their mental states. In this study, large amounts of Korean text were collected and analyzed to determine whether such data could be used to detect depression in users. This study analyzed data collected from Twitter users who had and did not have depressive tendencies between January 2016 and February 2019. The data for each user was separately analyzed before and after the appearance of depressive tendencies to see how their expression changed. In this study the data were analyzed through co-occurrence word analysis, topic modeling, and sentiment analysis. This study's automated data collection method enabled analyses of data collected over a relatively long period of time. Also it compared the textual characteristics of users with depressive tendencies to those without depressive tendencies.
Keywords
social media; text mining; twitter; depression; topic model; co-occurrence; sentiment analysis;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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