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Study of Mental Disorder Schizophrenia, based on Big Data

  • Hye-Sun Lee (Dept. of Occupational Therapy, Gwang-ju Women's Univ)
  • Received : 2023.10.10
  • Accepted : 2023.11.05
  • Published : 2023.12.31

Abstract

This study provides academic implications by considering trends of domestic research regarding therapy for Mental disorder schizophrenia and psychosocial. For the analysis of this study, text mining with the use of R program and social network analysis method have been used and 65 papers have been collected The result of this study is as follows. First, collected data were visualized through analysis of keywords by using word cloud method. Second, keywords such as intervention, schizophrenia, research, patients, program, effect, society, mind, ability, function were recorded with highest frequency resulted from keyword frequency analysis. Third, LDA (latent Dirichlet allocation) topic modeling result showed that classified into 3 keywords: patient, subjects, intervention of psychosocial, efficacy of interventions. Fourth, the social network analysis results derived connectivity, closeness centrality, betweennes centrality. In conclusion, this study presents significant results as it provided basic rehabilitation data for schizophrenia and psychosocial therapy through new research methods by analyzing with big data method by proposing the results through visualization from seeking research trends of schizophrenia and psychosocial therapy through text mining and social network analysis.

Keywords

Acknowledgement

This paper was supported by Research Funds of Kwangju Women's in KWU23-066

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