Research Article

A text mining analysis of customer evaluations in terms of gastronomy tourism

Volume: 24 Number: 46-1 December 31, 2021
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

  1. Akyol, İ. Ö. (2019). Elektronik ağızdan ağıza iletişim, Destinasyona yönelik Tutum, Destinasyon Ve Gastronomi imajının Turistlerin Ziyaret Niyetine Etkisi: Türkiye örneği (Doctoral dissertation, Marmara Universitesi (Turkey)).
  2. Arslan, E. (2020). Çevrimiçi Gastronomik Turist Deneyimlerinin İçerik Analiziyle İncelenmesi. AHBVÜ Turizm Fakültesi Dergisi, 23 (2), 442-460
  3. Avraham, E., & Ketter, E. (2016). Tourism marketing for developing countries: Battling stereotypes and crises in Asia, Africa and the Middle East. Springer.
  4. Beardsworth, A., & Keil, T. (2002). Sociology on the menu: An invitation to the study of food and society. Routledge.
  5. Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. the Journal of Machine Learning research, 3, 993-1022.
  6. Boyne, S., Williams, F., & Hall, D. (2003). On the trail of regional success: Tourism, food production and the Isle of Arran Taste Trail. In Tourism and gastronomy (pp. 105-128). Routledge.
  7. Büyükeke, A., Sökmen, A., & Gencer, C. (2020). Metin madenciliği ve duygu analizi yöntemleri ile sosyal medya verilerinden rekabetçi avantaj elde etme: Turizm sektöründe bir araştırma. Journal of Tourism and Gastronomy Studies, 8(1), 322-335.
  8. Cetin, G., & Bilgihan, A. (2016). Components of cultural tourists’ experiences in destinations. Current Issues in Tourism, 19(2), 137-154.

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

Cited By

Baun SOBED