Depression in South Korean Adolescents Captured by Text and Opinion Mining of Social Big Data
Depression in adolescence is recognized as an important social and public health issue that interferes with continued physical growth and increases the likelihood of other mental disorders. The goal of this study was to examine online documents posted by South Korean adolescents for 3 years through...
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Published in | International journal of environmental research and public health Vol. 20; no. 17; p. 6665 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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Abstract | Depression in adolescence is recognized as an important social and public health issue that interferes with continued physical growth and increases the likelihood of other mental disorders. The goal of this study was to examine online documents posted by South Korean adolescents for 3 years through the text and opinion mining of collectable documents in order to capture their depression. The sample for this study was online text-based individual documents that contained depression-related words among adolescents, and these were collected from 215 social media websites in South Korea from 1 January 2012 to 31 December 2014. A sentiment lexicon was developed for adolescent depressive symptoms, and such sentiments were analyzed through opinion mining. The depressive symptoms in the present study were classified into nine categories as suggested by the Diagnostic and Statistical Manual for Mental Disorders, 5th Edition (DSM-5). The association analysis and decision tree analysis of data mining were used to build an efficient prediction model of adolescent depression. Opinion mining indicated that 15.5% were emotionally stable, 58.6% moderately stressed, and 25.9% highly distressed. Data mining revealed that the presence of depressed mood most of the day or nearly every day had the greatest effect on adolescents’ depression. Social big data analysis may serve as a viable option for developing a timely response system for emotionally susceptible adolescents. The present study represents one of the first attempts to investigate depression in South Korean adolescents using text and opinion mining from three years of online documents that originally amounted to approximately 3.1 billion documents. |
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AbstractList | Depression in adolescence is recognized as an important social and public health issue that interferes with continued physical growth and increases the likelihood of other mental disorders. The goal of this study was to examine online documents posted by South Korean adolescents for 3 years through the text and opinion mining of collectable documents in order to capture their depression. The sample for this study was online text-based individual documents that contained depression-related words among adolescents, and these were collected from 215 social media websites in South Korea from 1 January 2012 to 31 December 2014. A sentiment lexicon was developed for adolescent depressive symptoms, and such sentiments were analyzed through opinion mining. The depressive symptoms in the present study were classified into nine categories as suggested by the Diagnostic and Statistical Manual for Mental Disorders, 5th Edition (DSM-5). The association analysis and decision tree analysis of data mining were used to build an efficient prediction model of adolescent depression. Opinion mining indicated that 15.5% were emotionally stable, 58.6% moderately stressed, and 25.9% highly distressed. Data mining revealed that the presence of depressed mood most of the day or nearly every day had the greatest effect on adolescents’ depression. Social big data analysis may serve as a viable option for developing a timely response system for emotionally susceptible adolescents. The present study represents one of the first attempts to investigate depression in South Korean adolescents using text and opinion mining from three years of online documents that originally amounted to approximately 3.1 billion documents. |
Author | Lee, Sangho Song, Juyoung Seo, Dong-Chul Song, Tae-Min |
AuthorAffiliation | 4 Department of Applied Health Science, Indiana University School of Public Health, Bloomington, IN 47405, USA 1 Administration of Justice, Pennsylvania State University, Schuylkill, PA 17972, USA; juyoung81@gmail.com 2 Gachon University Graduate School of Industry & Environment, Seoul 13120, Republic of Korea; tmsong01@hanmail.net 3 HealthMax Co., Ltd., Seoul 06078, Republic of Korea; lsh@healthmax.co.kr |
AuthorAffiliation_xml | – name: 3 HealthMax Co., Ltd., Seoul 06078, Republic of Korea; lsh@healthmax.co.kr – name: 1 Administration of Justice, Pennsylvania State University, Schuylkill, PA 17972, USA; juyoung81@gmail.com – name: 2 Gachon University Graduate School of Industry & Environment, Seoul 13120, Republic of Korea; tmsong01@hanmail.net – name: 4 Department of Applied Health Science, Indiana University School of Public Health, Bloomington, IN 47405, USA |
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Cites_doi | 10.1016/j.jadohealth.2018.10.298 10.1001/jama.293.20.2487 10.1192/bjp.bp.107.036079 10.1016/j.chb.2014.10.053 10.1145/1979742.1979489 10.1176/appi.ps.52.12.1615 10.1159/000319400 10.1002/da.20399 10.3349/ymj.2014.55.1.254 10.1016/j.jadohealth.2019.04.033 10.1542/peds.2011-0054 10.1176/appi.ajp.159.6.1051 10.1016/j.chb.2014.03.003 10.1016/j.jadohealth.2019.01.020 10.1002/da.22466 10.1073/pnas.1320040111 10.1016/j.jadohealth.2018.10.004 10.1016/j.chb.2015.08.023 10.1111/j.1600-0447.2011.01752.x 10.1111/1467-8721.ep10770953 10.1177/070674379704200904 |
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Title | Depression in South Korean Adolescents Captured by Text and Opinion Mining of Social Big Data |
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