TR
EN
A text mining analysis of customer evaluations in terms of gastronomy tourism
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 modeling, sentiment, and name-entity recognition analyzes 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.
Keywords
References
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Details
Primary Language
English
Subjects
Tourism (Other)
Journal Section
Research Article
Publication Date
December 31, 2021
Submission Date
November 17, 2021
Acceptance Date
December 20, 2021
Published in Issue
Year 2021 Volume: 24 Number: 46-1
APA
Büyükeke, A., & Özsoy, T. (2021). A text mining analysis of customer evaluations in terms of gastronomy tourism. Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 24(46-1), 1295-1312. https://doi.org/10.31795/baunsobed.1025204
AMA
1.Büyükeke A, Özsoy T. A text mining analysis of customer evaluations in terms of gastronomy tourism. BAUNSOBED. 2021;24(46-1):1295-1312. doi:10.31795/baunsobed.1025204
Chicago
Büyükeke, Ahmet, and Tufan Özsoy. 2021. “A Text Mining Analysis of Customer Evaluations in Terms of Gastronomy Tourism”. Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 24 (46-1): 1295-1312. https://doi.org/10.31795/baunsobed.1025204.
EndNote
Büyükeke A, Özsoy T (December 1, 2021) A text mining analysis of customer evaluations in terms of gastronomy tourism. Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 24 46-1 1295–1312.
IEEE
[1]A. Büyükeke and T. Özsoy, “A text mining analysis of customer evaluations in terms of gastronomy tourism”, BAUNSOBED, vol. 24, no. 46-1, pp. 1295–1312, Dec. 2021, doi: 10.31795/baunsobed.1025204.
ISNAD
Büyükeke, Ahmet - Özsoy, Tufan. “A Text Mining Analysis of Customer Evaluations in Terms of Gastronomy Tourism”. Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 24/46-1 (December 1, 2021): 1295-1312. https://doi.org/10.31795/baunsobed.1025204.
JAMA
1.Büyükeke A, Özsoy T. A text mining analysis of customer evaluations in terms of gastronomy tourism. BAUNSOBED. 2021;24:1295–1312.
MLA
Büyükeke, Ahmet, and Tufan Özsoy. “A Text Mining Analysis of Customer Evaluations in Terms of Gastronomy Tourism”. Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, vol. 24, no. 46-1, Dec. 2021, pp. 1295-12, doi:10.31795/baunsobed.1025204.
Vancouver
1.Ahmet Büyükeke, Tufan Özsoy. A text mining analysis of customer evaluations in terms of gastronomy tourism. BAUNSOBED. 2021 Dec. 1;24(46-1):1295-312. doi:10.31795/baunsobed.1025204