조현병 관련 주요 일간지 기사에 대한 텍스트 마이닝 분석
Text-Mining Analyses of News Articles on Schizophrenia
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OBJECTIVES In this study, we conducted an exploratory analysis of the current media trends on schizophrenia using text-mining methods. METHODS First, web-crawling techniques extracted text data from 575 news articles in10 major newspapers between 2018 and 2019, which were selected by searching “schizophrenia” in the Naver News. We had developed document-term matrix (DTM) and/or term-document matrix (TDM) through pre-processing techniques. Through the use of DTM and TDM, frequency analysis, cooccurrence network analysis, and topic model analysis were conducted. RESULTS Frequency analysis showed that keywords such as “police,” “mental illness,” “admission,” “patient,” “crime,” “apartment,” “lethal weapon,” “treatment,” “Jinju,” and “residents” were frequently mentioned in news articles on schizophrenia. Within the article text, many of these keywords were highly correlated with the term “schizophrenia” and were also interconnected with each other in the co-occurrence network. The latent Dirichlet allocation model presented 10 topics comprising a combination of keywords: “police-Jinju,” “hospital-admission,” “research-finding,” “care-center,” “schizophrenia-symptom,” “society-issue,” “family-mind,” “woman-school,” and “disabled-facilities.” CONCLUSION The results of the present study highlight that in recent years, the media has been reporting violence in patients with schizophrenia, thereby raising an important issue of hospitalization and community management of patients with schizophrenia.
Abstract
OBJECTIVES In this study, we conducted an exploratory analysis of the current media trends on schizophrenia using text-mining methods. METHODS First, web-crawling techniques extracted text data from 575 news articles in10 major newspapers between 2018 and 2019, which were selected by searching “schizophrenia” in the Naver News. We had developed document-term matrix (DTM) and/or term-document matrix (TDM) through pre-processing techniques. Through the use of DTM and TDM, frequency analysis, cooccurrence network analysis, and topic model analysis were conducted. RESULTS Frequency analysis showed that keywords such as “police,” “mental illness,” “admission,” “patient,” “crime,” “apartment,” “lethal weapon,” “treatment,” “Jinju,” and “residents” were frequently mentioned in news articles on schizophrenia. Within the article text, many of these keywords were highly correlated with the term “schizophrenia” and were also interconnected with each other in the co-occurrence network. The latent Dirichlet allocation model presented 10 topics comprising a combination of keywords: “police-Jinju,” “hospital-admission,” “research-finding,” “care-center,” “schizophrenia-symptom,” “society-issue,” “family-mind,” “woman-school,” and “disabled-facilities.” CONCLUSION The results of the present study highlight that in recent years, the media has been reporting violence in patients with schizophrenia, thereby raising an important issue of hospitalization and community management of patients with schizophrenia.
참고문헌 (29)
- "Government announces measures to deal with mental illness in light of rise in crimes" (2019)[URL]
- "Statement from the Korean Society for Schizophrenia Research on the police officer killed" (2018)[URL]
- Corrigan P, "How stigma interferes with mental health care", Am Psychol, 59, pp.614~625 (2004)
- Lauber C, "Stigma towards people with mental illness in developing countries in Asia", Int Rev Psychiatry, 19, pp.157~178 (2007)
- Corrigan PW, "Lessons from social psychology on discrediting psychiatric stigma", Am Psychol, 54, pp.765~776 (1999)
- 박종익, "정신질환에 대한 사회적 편견", 신경정신의학, 55(4), pp.299~309 (2016), 대한신경정신의학회[DOI]
- Goepfert NC, "Effects of stigmatizing media coverage on stigma measures, self-esteem, and affectivity in persons with depression-an experimental controlled trial", BMC Psychiatry, 19, pp.138~ (2019)
- Krippendorff K, "Content analysis: an introduction to its methodology" (2013), Sage
- Rajman M, "Data mining and reverse engineering", pp.50~64 (1998), Springer
- Cho J, "Efficient crawling through URL ordering", Comput Netw Isdn Sys, 30, pp.161~172 (1998)
- Wickham H, "rvest: Easily Harvest (Scrape) Web Pages. R package version 0.3.4", ~ (2019)
- Feinerer I, "tm: Text Mining Package. R package version 0.7-6", ~ (2018)
- Jeon H, "KoNLP: Korean NLP Package. R package version 0.80.1", ~ (2016)
- Baek YM, "Ext-mining using R" (2017), Hanulmplus
- Lang D, "wordcloud2: create word cloud by ‘htmlwidget’. R package version 0.2.1", ~ (2018)
- 이수상, "언어 네트워크 분석 방법을 활용한 학술논문의 내용분석", 정보관리학회지, 31(4), pp.49~68 (2014), 한국정보관리학회[DOI]
- Epskamp S, "Qgraph : network visualizations of relationships in psychometric data", J Stat Softw, 48, pp.18~ (2012)
- Blei DM, "A correlated topic model of science", Ann Appl Stat, 1, pp.17~35 (2007)
- Blei DM, "Latent dirichlet allocation", J Mach Learn Res, 3, pp.993~1022 (2003)
- Roberts M, "Stm : R package for structural topic models", J Stat Softw, 91, pp.1~40 (2019)
- Chang J, "Lda: collapsed Gibbs sampling methods for topic models. R package version 1.4.2", ~ (2015)
- Griffiths TL, "Finding scientific topics", Proc Natl Acad Sci U S A, 101(Suppl 1), pp.5228~5235 (2004)
- Kim SW, "The analysis of newspaper-articles on psychosis", J Korean Neuropsychiatr Assoc, 39, pp.838~848 (2000)
- Lee MS, "Trend of internet media report for mental health and suicide", J Korean Assoc Soc Psychiatry, 14, pp.97~104 (2009)
- 백혜진, "정신질환의 낙인과 귀인에 대한 언론 보도 분석", 한국언론학보, 61(4), pp.7~43 (2017), 한국언론학회[DOI]
- 황애리, "한국 언론의 정신건강 보도에 관한 내용 분석 연구: 뉴스 프레임과 기사 논조를 중심으로", 보건사회연구, 38(4), pp.290~322 (2018), 한국보건사회연구원[DOI]
- 최정원, "텍스트마이닝 방법론을 활용한 기업 부도 예측 연구", 생산성연구: 국제융합학술지, 29(1), pp.201~228 (2015), 한국생산성학회[DOI]
- 강범일, "토픽 모델링을 이용한 신문 자료의 오피니언 마이닝에 대한 연구", 한국문헌정보학회지, 47(4), pp.315~334 (2013), 한국문헌정보학회[DOI]
- Koike S, "Effect of name change of schizophrenia on mass media between 1985 and 2013in Japan : a text data mining analysis", Schizophr Bull, 42, pp.552~559 (2016)