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조현병 관련 주요 일간지 기사에 대한 텍스트 마이닝 분석

Text-Mining Analyses of News Articles on Schizophrenia

  • 남희정 (서울의료원 정신건강의학과) ;
  • 류승형 (전남대학교 의과대학 정신건강의학교실)
  • Nam, Hee Jung (Department of Psychiatry, Seoul Medical Center) ;
  • Ryu, Seunghyong (Department of Psychiatry, Chonnam National University Medical School)
  • 투고 : 2020.04.29
  • 심사 : 2020.08.07
  • 발행 : 2020.10.30

초록

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 in 10 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, co-occurrence 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.

키워드

과제정보

본 연구는 2018년도 대한조현병학회 연구기금 연구비의 지원을 받아 수행된 연구임.

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