Evaluation of tourist reviews on TripAdvisor for the protection of the world heritage sites: Text mining approach

Yıl 2021, Cilt: 6 Sayı: 1, 37 - 46, 31.07.2021

Akın Özen

https://doi.org/10.31822/jomat.876175

Cited By: 9

Öz

Collecting and analyzing online tourist reviews on destinations is important for sustainable tourism. These analyses can give insight into the extent to which natural and cultural assets in the destination are protected. These evaluations should be considered by the authorities as objective and realistic assessments. In this study, 4183 TripAdvisor reviews of foreign tourists visiting “Göreme National Park and Cappadocia Rocky Area”, which is listed in the World Heritage Site, were evaluated. The data set consisted of English reviews of foreign tourists visiting the region between the years of 2018 - 2020. Dictionary-based sentiment analysis, one of the text mining methods, was used in the study. According to the analysis results, the positive perceptions of the tourists about the churches, fairy chimneys, valleys and underground cities in the World Heritage Site were found to be significantly high (75%). Negative evaluations were found to be low (33%). In tourist reviews, 63% positive and 10.49% negative evaluations were made about the protection of the region. In addition, the awareness of the tourists about whether the locations they visit are World Heritage Sites was 30.6%. Tourists explained their negative opinions about the locations they visited with the words "extra_payment", "crowded", and "steep". Another finding of the study was that the area is adequately protected. There were, however, some concerns related to protection. The most striking aspects of protection concerns were those in which the words "painted" and "drawn" were used, an important indicator of visitor sensitivity to the protection of frescoes in rock churches. Since the destruction of natural and cultural assets in the region is unacceptable, recommendations are made to take the necessary measures to prevent such damage.

Anahtar Kelimeler

World Heritage, Text mining, Dictionary-based Sentiment Analysis, Cappadocia, Göreme

Kaynakça

• Akbıyık, A. (2019). Sosyal Bilimlerde Metin Madenciliği. Sakarya Yayıncılık.
• Akipek, S. (2001). Dünya kültürel ve doğal mirasının korunmasına dair sözleşmenin değerlendirilmesi. Ankara Üniversitesi Hukuk Fakültesi Dergisi, 50(4), 13–39.
• Antonio, N., Correia, M. B., & Ribeiro, F. P. (2020). Exploring User-Generated Content for Improving Destination Knowledge: The Case of Two World Heritage Cities. Sustainability, 12(22), 9654. https://doi.org/10.3390/su12229654
• Artola, C., Pinto, F., & Pedraza, P. De. (2015). Can internet searches forecast tourism inflows? International Journal of Manpower, 36(1), 103–116. https://doi.org/10.1108/IJM-12-2014-0259
• Aydın, B. (2016). Restaurant Image in Social Media: The Case of Tripadvisor. Journal of Multidisciplinary Academic Tourism, 1(1), 13–30. https://doi.org/10.31822/jomat.287998
• Buzova, D., Sanz-Blas, S., & Cervera-Taulet, A. (2019). Does culture affect sentiments expressed in cruise tours’ eWOM? The Service Industries Journal, 39(2), 154–173. https://doi.org/10.1080/02642069.2018.1476497
• Çeşmeci, N., & Tekeli, E. K. (2018). Göreme Tarihi Milli Parkı’nın Sürdürülebilir Turizm Açısından Değerlendirilmesi. Turan Stratejik Arastirmalar Merkezi Dergisi, 10(40), 148. https://doi.org/http://dx.doi.org/10.15189/1308-8041
• De Luca, G., Shirvani Dastgerdi, A., Francini, C., & Liberatore, G. (2020). Sustainable Cultural Heritage Planning and Management of Overtourism in Art Cities: Lessons from Atlas World Heritage. Sustainability, 12(9), 3929. https://doi.org/10.3390/su12093929
• Demirçivi, B. M. (2017). Göreme Millî Parkı ve Kapadokya Kayalık Bölgeleri’ne İlişkin UNESCO Raporu Değerlendirmeleri ve Öneriler. Turizm Akademik Dergisi, 4(2), 91–106. https://dergipark.org.tr/en/pub/touraj/issue/33509/356565
• Denizci Guillet, B., Kucukusta, D., & Liu, L. (2016). An Examination of Social Media Marketing in China: How do the Top 133 Hotel Brands Perform on the Top Four Chinese Social Media Sites? Journal of Travel & Tourism Marketing, 33(6), 783–805. https://doi.org/10.1080/10548408.2015.1064337
• Dinis, M. G. F., da Costa, C. M. M., & Pacheco, O. M. da R. (2019). Composite indicators for measuring the online search interest by a tourist destination. In Big Data and Innovation in Tourism, Travel, and Hospitality: Managerial Approaches, Techniques, and Applications (pp. 1–19). Springer Singapore. https://doi.org/10.1007/978-981-13-6339-9_1
• Doğan, N. Ö., & Karakuş, Y. (2014). Evaluating the service quality in the tourism industry using QFD-AHP integrated method: an application on Göreme Open Air Museum. In Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi (Vol. 19, Issue 3). SDÜ İktisadi ve İdari Bilimler Fakültesi.
• Gunter, U., & Önder, I. (2016). Forecasting city arrivals with Google Analytics. Annals of Tourism Research, 61, 199–212. https://doi.org/10.1016/j.annals.2016.10.007 Hu, M., & Liu, B. (2004). Mining and summarizing customer reviews. Proceedings of the 2004 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD ’04, 168. https://doi.org/10.1145/1014052.1014073
• Irawan, H., Akmalia, G., & Masrury, R. A. (2019). Mining tourist’s perception toward Indonesia tourism destination using sentiment analysis and topic modelling. ACM International Conference Proceeding Series, 7–12. https://doi.org/10.1145/3361821.3361829
• Jo, Y., & Oh, A. H. (2011). Aspect and sentiment unification model for online review analysis. Proceedings of the Fourth ACM International Conference on Web Search and Data Mining - WSDM ’11, 815. https://doi.org/10.1145/1935826.1935932
• Karakuş, Y., & Kalay, N. (2017). A Study on The Concept and Causes of Destination Rejection. International Journal of Management Economics and Business, 13(3), 1–16. https://doi.org/http://dx.doi.org/10.17130/ijmeb.2017331320
• Kim, K., Park, O. joung, Yun, S., & Yun, H. (2017). What makes tourists feel negatively about tourism destinations? Application of hybrid text mining methodology to smart destination management. Technological Forecasting and Social Change, 123, 362–369. https://doi.org/10.1016/j.techfore.2017.01.001
• Kiritchenko, S., Zhu, X., & Mohammad, S. M. (2014). Sentiment Analysis of Short Informal Texts. Journal of Artificial Intelligence Research, 50, 723–762. https://doi.org/10.1613/jair.4272
• Li, Q., Li, S., Zhang, S., Hu, J., & Hu, J. (2019). A review of text corpus-based tourism big data mining. Applied Sciences (Switzerland), 9(16). https://doi.org/10.3390/app9163300
• Liu, M. T., Liu, Y., Mo, Z., & Ng, K. L. (2020). Using text mining to track changes in travel destination image: the case of Macau. Asia Pacific Journal of Marketing and Logistics, 33(2), 379–395. https://doi.org/10.1108/APJML-08-2019-0477
• Medhat, W., Hassan, A., & Korashy, H. (2014). Sentiment analysis algorithms and applications: A survey. Ain Shams Engineering Journal, 5(4), 1093–1113. https://doi.org/10.1016/j.asej.2014.04.011
• Miner, G., Elder IV, J., Fast, A., Hill, T., Nisbet, R., & Delen, D. (2012). Practical text mining and statistical analysis for non-structured text data applications. Academic Press. Munar, A. M. (2012). Social Media Strategies and Destination Management. Scandinavian Journal of Hospitality and Tourism, 12(2), 101–120. https://doi.org/10.1080/15022250.2012.679047
• Oğuzlar, A., & Kızılkaya, Y. M. (2019). Metin Madenciliğinde Duygu Analizi. Dora Yayıncılık.
• Özen, İ. A., & İlhan, İ. (2020). Opinion Mining in Tourism: A Study on ”Cappadocia Home Cooking” Restaurant. In E. Çeltek (Ed.), Handbook of Research on Smart Technology Applications in the Tourism Industry (pp. 43–64). IGI Global.
• Pan, B., Wu, D. C., & Song, H. (2012). Forecasting hotel room demand using search engine data. Journal of Hospitality and Tourism Technology, 3(3), 196–210. https://doi.org/10.1108/17579881211264486
• Schmunk, S., Höpken, W., Fuchs, M., & Lexhagen, M. (2013). Sentiment Analysis: Extracting Decision-Relevant Knowledge from UGC. In Information and Communication Technologies in Tourism 2014 (pp. 253–265). Springer International Publishing. https://doi.org/10.1007/978-3-319-03973-2_19
• Su, M. M., & Wall, G. (2011). Chinese Research on World Heritage Tourism. Asia Pacific Journal of Tourism Research, 16(1), 75–88. https://doi.org/10.1080/10941665.2011.539392
• Topsakal, Y. (2018). Akıllı Turizm Kapsamında Engelli Dostu Mobil Hizmetler: Türkiye 4.0 İçin Öneriler. Journal of Tourism Intelligence and Smartness, 1(1), 1–13. https://dergipark.org.tr/en/pub/jtis/issue/39024/445128
• Tosun, C., Dedeoğlu, B. B., Çalışkan, C., & Karakuş, Y. (2020). Role of place image in support for tourism development: The mediating role of multi‐dimensional impacts. International Journal of Tourism Research, jtr.2405. https://doi.org/10.1002/jtr.2405
• UNESCO. (2020). UNESCO World Heritage Centre - World Heritage List Statistics. UNESCO. http://whc.unesco.org/en/list/stat Uşaklı, A., Koç, B., & Sönmez, S. (2019). Social Media Usage Among Top European DMOs. In In Tourist Destination Management (pp. 1–14). Springer, Cham. https://doi.org/10.1007/978-3-030-16981-7_1
• Yılmaz, İ. (2011). Müze ziyaretçilerinin hizmet kalitesi algılamaları: Göreme Açık Hava Müzesi örneği. Anatolia: Turizm Araştırmaları Dergisi, 22(2), 183–193. https://dergipark.org.tr/en/pub/atad/issue/16802/174525
• Yılmaz, İ., Tabak, G., & Samur, A. N. (2020). Vandalism problem in tourism and solution proposals: The case of Nevşehir. Journal of Multidisciplinary Academic Tourism, 5(2), 95–103. https://doi.org/10.31822/jomat.706294