The process to assess a hospital performance usually needs the interaction of a lot of experts and patients and is very costly and time-consuming. Nevertheless, the availability of patient opinions on the Internet offers a great opportunity to develop systems that evaluate hospitals based on user feedback. The content of these opinions is very challenging, including information about the hospital services but also stories about their own patients, their families, and personal feelings or beliefs before or after leaving a hospital. Therefore, the task of recommending hospitals according to the quality of their services becomes really complicated. This study describes an application for ranking hospitals based on the user preferences about the different offered services as well as the opinions about them. First, it semiautomatically classifies all predefined hospital aspects, calculates the sentiment orientation, and represents their associated polarity by intuitionistic fuzzy sets. Second, by means of the user preferences towards the different aspects, an aggregation operator, and a multicriteria decision-making algorithm, all hospitals are ranked. To assess this methodology, a large set of reviews about hospitals have been collected.
Measuring what hospital offers the best services is very difficult, for that reason, the opinions from previous patients have become an essential tool for the new possible clients to decide which services they must select. Many online platforms deal with opinions to analyze their services/products, primarily, by means of aspect-based sentiment analysis techniques. These techniques are mainly based on the detection of features from services/products to model the feelings toward them. Most models primarily cope with positiveness, negativeness and neutrality; nevertheless, these do not reflect other situations in which there are positive and negative aspects, but the overall sentiment is not neutral, but indeterminate. To face this issue, simplified neutrosophic sets can be a useful tool. Therefore, this study presents a novel application of the simplified neutrosophic sets to hospital ranking. The application, first, detects the hospital features, second, models the feelings toward them using simplified neutrosophic sets, and finally, ranks the hospitals according to the patients’ preferences. It has been tested using opinions from a real website and compared against other fuzzy logic-based approaches. The achieved results outperform the ones obtained by other proposals, revealing that simplified neutrosophic sets can be an interesting solution to model feelings.
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