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KMID : 1151020190470040034
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Mental Health & Social Work
2019 Volume.47 No. 4 p.34 ~ p.53
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the Perception of schizophrenia Using Big Dat
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Ju So-Hee
Lee Kyung-Eun
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Abstract
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we want to use big data to understand the public's perception of schizophrenia through the public's semantic connection structure. I want to see what the general public has in mind about schizophrenia and what kind of image or recognition it creates. This study used text mining to grasp meanings of words related to schizophrenia recognized over the past decade at context level, semantic network analysis to find key words based on relationships between words, and CONCOR analysis method to find groups of words connected at the same time as words. The results of this study show that the first, the high frequency of core words, the public, was mainly represented by words related to diseases such as schizophrenia, patients, treatment, mental disorders, diagnosis, medicine, and auditory delusions. Second, network analysis strongly showed that the public has a strong causal perception that schizophrenia is a patient and at the same time Third, Group I is the words for treatment and symptom related to schizophrenia, and the words in Group II and III are composed of the crimes and events resulting from schizophrenia. IV Group 4 formed a central network of words in dramas and movies. The study found that the public recognized Cho-hyeon's perceptions as "sick or bad" and that no human rights, rehabilitation or social return-related perceptions of patients with schizophrenia appeared. Therefore, the public proposed an alternative to recognizing schizophrenia as 'people-centered' rather than 'event-oriented'.
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KEYWORD
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Patients with schizophrenia, Rehabilitation, Social Recognition, Big Data Analysis
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FullTexts / Linksout information
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Listed journal information
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