국내 언론에 나타난 정신질환 관련 이슈의 언어 네트워크 분석 : 2016년부터 2018년까지 주요 5대 언론사를 중심으로

• 영문명: Semantic Network Analysis of Iussues Related to Mental Illness in Korea Media : Focusing on the Five Major Media from 2016 to 2018
• 발행기관: 대한신경정신의학회
• 저자명: 박선주(Sun Joo Park) 신나리(Na Ri Shin) 김승혜(Seung Hye Kim) 박수빈(Su Bin Park) 김철응(Chul Eung Kim)
• 간행물 정보: 『신경정신의학』제59권 제1호, 72~85쪽, 전체 14쪽
• 주제분류: 의약학 > 정신과학
• 파일형태: PDF
• 발행일자: 2020.02.28

영문 초록

Objectives This study examined the trend of press reports on mental illness in Korea to help set a desirable direction for future press reports on the subject. Methods This study adopted the method of semantic network analysis to analyze the trend of press reporting on mental illness in Korea. The study analyzed 1253 newspaper articles from 2016 to 2018 published by the five major Korean press : The Kyunghyang Shinmun, The Dong-A Ilbo, The Chosun Ilbo, The JoongAng Ilbo, and The Hankyoreh. Results The number of articles on mental illness is on the decline year by year, with 465 articles in 2016, 406 in 2017, and 382 in 2018. According to keyword analysis, the order of the words of the highest frequency is as follows : treatment (659), patients (486), mental health (466), incidents (436), and children and adolescents (413). In terms of the Degree Centrality, Closeness Centrality, and Betweenness Centrality, the following words are commonly ranked within the top 10 on the lists: treatment, children and adolescents, patient, mental health, depressive disorder, family, suicide, and counselling. Conclusion The press should pay more attention to mental illness, and its reporting should guarantee accuracy, objectivity, fairness, diversity, and social responsibility. In addition, reports on mental illness need to provide balanced health information, considering the readers, from basic information on mental illness to detailed treatment methods. Establishing reporting guidelines for mental illness would help reduce harm and prejudice related to mental illness and increase access to treatment.

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Mental illness Semantic network analysis Newspaper articles