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조현병 관련 주요 일간지 기사에 대한 텍스트 마이닝 분석

Text-Mining Analyses of News Articles on Schizophrenia

대한조현병학회지 2020년 23권 2호 p.58 ~ 64
남희정, 류승형,
소속 상세정보
남희정 ( Nam Hee-Jung ) - Seoul Medical Center Department of Psychiatry
류승형 ( Ryu Seung-Hyong ) - Chonnam National University Medical School Department of Psychiatry

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.

키워드

Media; News; Schizophrenia; Text-mining; Violence

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