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

Author

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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)

  • OA Alghamdi

    (��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)

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.

Suggested Citation

  • Mehrbakhsh Nilashi & Sarminah Samad & Abdullah Alghamdi & Muhammed Yousoof Ismail & OA Alghamdi & Syed Salman Mehmood & Saidatulakmal Mohd & Waleed Abdu Zogaan & Ashwaq Alhargan, 2022. "A New Method for Analysis of Customers’ Online Review in Medical Tourism Using Fuzzy Logic and Text Mining Approaches," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 21(06), pages 1797-1820, December.
    • Handle: RePEc:wsi:ijitdm:v:21:y:2022:i:06:n:s0219622022500341
    DOI: 10.1142/S0219622022500341
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