Fusing hotel ratings and reviews with hesitant terms and consensus measures
- PDF / 527,806 Bytes
- 11 Pages / 595.276 x 790.866 pts Page_size
- 103 Downloads / 150 Views
(0123456789().,-volV)(0123456789().,-volV)
S.I.: ARTIFICIAL INTELLIGENCE INTERNATIONAL CONFERENCE - A2IC 2018
Fusing hotel ratings and reviews with hesitant terms and consensus measures Jennifer Nguyen1 • Jordi Montserrat-Adell2 • Nu´ria Agell2 • Monica Sa´nchez1 • Francisco J. Ruiz1 Received: 21 January 2019 / Accepted: 7 February 2020 Ó Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract People have come to refer to reviews for valuable information on products before making a purchase. Digesting relevant opinions regarding a product by reading all the reviews is challenging. An automated methodology which aggregates opinions across all the reviews for a single product to help differentiate any two products having the same overall rating is defined. In order to facilitate this process, rating values, which capture the overall satisfaction, and written reviews, which contain the sentiment of the experience with a product, are fused together. In this manner, each reviewer’s opinion is expressed as an interval rating by means of hesitant fuzzy linguistic term sets. These new expressions of opinion are then aggregated and expressed in terms of a central opinion and degree of consensus representing the agreement among the sentiment of the reviewers for an individual product. A real case example based on 2506 TripAdvisor reviews of hotels in Rome during 2017 is provided. The efficiency of the proposed methodology when discriminating between two hotels is compared with the TripAdvisor rating and median of reviews. The proposed methodology obtains significant differentiation between product rankings. Keywords Hesitant fuzzy linguistic term sets Linguistic decision making Consensus models Tourism Reviews
1 Introduction Marketing research has found that consumers influence each other in their decision-making process [4]. On internet platforms, this influence is derived from ratings and reviews [2]. These reviews facilitate the decision-making process between people using the same platform, particularly in the case of experiential good. Consumer reviews are important for products such as destinations, hotels, and restaurants because it is difficult for people to assess their quality before consuming them [14]. Hence, online ratings and reviews serve as a word-of-mouth providing indirect experiences to interested consumers [36]. According to & Nu´ria Agell [email protected] 1
Universitat Polite`cnica de Catalunya - BarcelonaTech, Edifici Omega, Despatx 342, C. Jordi Girona, 1-3, 08034 Barcelona, Spain
2
ESADE Business School, Ramon Llull University, 59 Av. Torreblanca, 08172 Sant Cugat, Spain
Nielsen,1 70% of social media users go online to read about other people’s experiences with an item at least once a month. Several online communities such as Tripadvisor,2 Yelp,3 and Booking4 have become a preferred source of information in tourism and hospitality. However, while these communities facilitate consumers’ search for information, it is difficult for them to process and judge it [14]. When o
Data Loading...
