Hesitancy and consensus measures to understand ratings: an application to hotel recommendations
| Autor: | Jennifer, Nguyen, Montserrat Adell, Jordi, Agell Jané, Núria, Sánchez Soler, Monica, Ruiz Vegas, Francisco Javier |
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| Přispěvatelé: | Universitat Politècnica de Catalunya. Departament de Matemàtiques, Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya. GREC - Grup de Recerca en Enginyeria del Coneixement |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Sentiment analysis
Group Decision-Making (GDM) Degree of consensus Decisió Presa de Turisme Hesitant Fuzzy Linguistic Term Sets (HFLTSs) Matemàtiques i estadística::Matemàtica aplicada a les ciències [Àrees temàtiques de la UPC] Computational linguistics Lingüística computacional Decision making 68 Computer science::68T Artificial intelligence [Classificació AMS] Tourism |
| ISSN: | 2016-8004 |
| Popis: | When searching for recommendations online, users are often presented with similar items all having the same ratings. It is left to the user to discern which rated item is best from other information. In order to facilitate this process, we propose a new methodology to associate a measure of consensus to the ratings derived from a group of reviewers. The opinion of reviewers are considered not only from rating values but from written reviews. This allows us to express reviewer opinions as interval ratings by means of hesitant fuzzy linguistic term sets and compute a consensus. A real case example is provided to show the potential of the proposed methodology. The example provided is based on 966 TripAdvisor reviews of the twenty most reviewed hotels during 2017 in Rome at the time the data was taken. The consensus measure allows us to better understand hotel reviews. This research has been partially supported by the Secretary of Universities and Research of the Department of Enterprise and Knowledge of the Generalitat de Catalunya (2017 DI 086) and by the INVITE Research Project (TIN2016- 80049-C2-1-R and TIN2016-80049-C2-2-R (AEI/FEDER, UE)), funded by the Spanish Ministry of Science and Information Technology. |
| Databáze: | OpenAIRE |
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