A text mining analysis of customer evaluations in terms of gastronomy tourism
dc.contributor.author | Büyükeke, Ahmet | |
dc.contributor.author | Özsoy, Tufan | |
dc.date.accessioned | 2025-01-06T17:23:21Z | |
dc.date.available | 2025-01-06T17:23:21Z | |
dc.date.issued | 2021 | |
dc.department | Adana Alparslan Türkeş Bilim ve Teknoloji Üniversitesi | |
dc.description.abstract | Nutritional alternatives, which were limited to regional diversity in the past, have increased extraordinarily over time. Besides being the basic element to sustain life, it has come to the fore as hedonic consumption. It is already known that discovering the local cuisine and the pleasure of eating are very important for tourists. Social media platforms have become the most effective tool for tourists in making decisions. They significantly influence the decisions of tourists on where to go, where to stay, what to eat and drink. The primary aim of this research is to analyze and make sense of TripAdvisor reviews of restaurants serving Kaş and Belek, which have different accommodation alternatives. For this purpose, topic modelling, sentiment, and name-entity recognition analyses were carried out with 10,829 customer comments from 147 businesses. Reviews are clustered under the most appropriate 3 distinct subjects (Experience, Food, and Atmosphere). The satisfaction level in the comments is 89.52% for Kaş and 95.64% for Belek. In total, 800 and 445 different food names were discovered in Kaş and Belek reviews, respectively. Most liked foods: Meat dishes such as steak, burger, and stroganoff with cream, pepper, tomato, garlic, and spicy sauces. | |
dc.identifier.doi | 10.31795/baunsobed.1025204 | |
dc.identifier.endpage | 1311 | |
dc.identifier.issn | 1301-5265 | |
dc.identifier.issn | 2651-4974 | |
dc.identifier.issue | 46-1 | |
dc.identifier.startpage | 1295 | |
dc.identifier.trdizinid | 1107519 | |
dc.identifier.uri | https://doi.org/10.31795/baunsobed.1025204 | |
dc.identifier.uri | https://search.trdizin.gov.tr/tr/yayin/detay/1107519 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14669/737 | |
dc.identifier.volume | 24 | |
dc.indekslendigikaynak | TR-Dizin | |
dc.language.iso | en | |
dc.relation.ispartof | Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi | |
dc.relation.publicationcategory | Makale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.snmz | KA_20241211 | |
dc.subject | Text mining | |
dc.subject | Gastronomy | |
dc.subject | Food tourism | |
dc.subject | Customer reviews | |
dc.title | A text mining analysis of customer evaluations in terms of gastronomy tourism | |
dc.type | Article |