The Journal of Korean Medicine (대한한의학회지)

The Society of Korean Medicine (대한한의학회)
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Reviews Analysis of Korean Clinics Using LDA Topic Modeling

토픽 모델링을 활용한 한의원 리뷰 분석과 마케팅 제언

  • 김초명 (경희대학교 대학원 의료경영학과) ;
  • 조아람 (경희대학교 대학원 경영학과) ;
  • 김양균 (경희대학교 대학원 의료경영학과)
  • Received : 2022.02.11
  • Accepted : 2022.02.22
  • Published : 2022.03.01
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Abstract

Objectives: In the health care industry, the influence of online reviews is growing. As medical services are provided mainly by providers, those services have been managed by hospitals and clinics. However, direct promotions of medical services by providers are legally forbidden. Due to this reason, consumers, like patients and clients, search a lot of reviews on the Internet to get any information about hospitals, treatments, prices, etc. It can be determined that online reviews indicate the quality of hospitals, and that analysis should be done for sustainable hospital marketing. Method: Using a Python-based crawler, we collected reviews, written by real patients, who had experienced Korean medicine, about more than 14,000 reviews. To extract the most representative words, reviews were divided by positive and negative; after that reviews were pre-processed to get only nouns and adjectives to get TF(Term Frequency), DF(Document Frequency), and TF-IDF(Term Frequency - Inverse Document Frequency). Finally, to get some topics about reviews, aggregations of extracted words were analyzed by using LDA(Latent Dirichlet Allocation) methods. To avoid overlap, the number of topics is set by Davis visualization. Results and Conclusions: 6 and 3 topics extracted in each positive/negative review, analyzed by LDA Topic Model. The main factors, consisting of topics were 1) Response to patients and customers. 2) Customized treatment (consultation) and management. 3) Hospital/Clinic's environments.

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References

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