A New Method for Analysis of Customers’ Online Review in Medical Tourism Using Fuzzy Logic and Text Mining Approaches

Mehrbakhsh Nilashi, Sarminah Samad, Abdullah Alghamdi, Muhammed Yousoof Ismail, Alghamdi Oa, Syed Salman Mehmood, Saidatulakmal Mohd, Waleed Abdu Zogaan and Ashwaq Alhargan
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Mehrbakhsh Nilashi: UCSI Graduate Business School, UCSI University, No. 1 Jalan Menara Gading, UCSI Heights, Cheras 56000, Kuala Lumpur, Malaysia†Centre for Global Sustainability Studies (CGSS), Universiti Sains Malaysia, 11800 USM Penang, Malaysia
Sarminah Samad: ��Department of Business Administration, College of Business and Administration, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
Abdullah Alghamdi: �Information Systems Dept., College of Computer Science and Information Systems, Najran University, Najran, Saudi Arabia
Muhammed Yousoof Ismail: �Department of MIS, Dhofar University, Oman
Alghamdi Oa: ��Business Administration Dept., Applied College, Najran University, Najran, Saudi Arabia
Syed Salman Mehmood: *Department of Mathematics, Abu Dhabi University, United Arab Emirates
Saidatulakmal Mohd: ��†Centre for Global Sustainability Studies & School of Social Sciences, Universiti Sains, Malaysia
Waleed Abdu Zogaan: ��‡Department of Computer Science, Faculty of Computer Science and Information Technology, Jazan University, Jazan 45142, Saudi Arabia
Ashwaq Alhargan: �§Computer Science Department, College of Computing and Informatics, Saudi Electronic University, Saudi Arabia

International Journal of Information Technology & Decision Making (IJITDM), 2022, vol. 21, issue 06, 1797-1820

Abstract: Mining medical tourists’ preferences and detecting their satisfaction level through Electronic Word of Mouth (eWOM) in medical tourism websites is an important task. Machine learning techniques have been very successful in developing recommendation agents through the analysis of eWOM in the e-commerce context. However, such methods are fairly unexplored in the medical tourism context through the analysis of user-generated content. This research is the first attempt to analyze eWOM in medical tourism websites for tourists’ preferences mining using machine learning techniques. The results of the eWOM analysis revealed that the learning techniques are able to effectively analyze online reviews and accurately predict their preferences for their decision-making process in medical tourism. Compared to the methods which rely solely on the supervised learning techniques, the method evaluation results demonstrated that the use of fuzzy clustering and text mining approaches can be an important stage of eWOM analysis in the prediction of medical tourists’ preferences.

Keywords: Neuro–fuzzy; fuzzy set theory; fuzzy clustering; medical tourism; tourist preference (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0219622022500341

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