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KMID : 0603920200280030039
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Journal of Korean Academy of Occupational Therapy
2020 Volume.28 No. 3 p.39 ~ p.51
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Analysis of Occupational Therapy-Related Keywords Using Text Mining
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Jo Eun-Ju
Kam Kyung-Yoon
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Abstract
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Objective: The purpose of this study is to analyze the keywords related to occupational therapy on popular websites of major portal sites. According to an analysis of the most frequent keywords, we tried to describe the stateand general awareness of occupational therapy in Korea.
Methods: For this purpose, news, blogs, cafes, and Jishik-in/Daum tips provided by Naver, Daum, and Google wereselected as channels for analysis. The keyword to be extracted from texts in these channels was “occupationaltherapy.” The semantic network including degree centrality, betweenness centrality, community, and co-currentwords were analyzed using the Netminer program (ver. 4). Only nouns were subjected to the analyses.
Results: “Occupational therapy” (14,624), “therapy” (13,530), “occupation” (7,470), “hospital” (4,618), “occupationaltherapist” (3,612), and “rehabilitation” (3,193) were the top-5 frequently appearing keywords. There were similarresults in the degree centrality and the betweenness centrality. Occupational therapy/physical therapy (997),convalescence/hospital (783), occupational therapy/speech therapy (564), and occupational therapy/program (510)were shown in most of the frequent co-current keywords. Seven groups were clustered in the communityanalysis.
Conclusion: Through this study, it was found that occupational therapy is recognized as a “rehabilitation” for“disabled people” in “hospitals” in Korea, and the role of occupational therapy for “dementia” is expected. Therecognition that it is closely related to other rehabilitation areas suggests that occupational therapy needs toestablish its status in the rehabilitation field.
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KEYWORD
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Big data, Semantic network, Occupational therapy, Text-mining
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FullTexts / Linksout information
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Listed journal information
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