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‘You will like it!’ using open data to predict tourists' response to a tourist attraction

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  • Pantano, Eleonora
  • Priporas, Constantinos-Vasilios
  • Stylos, Nikolaos

Abstract

The increasing amount of user-generated content spread via social networking services such as reviews, comments, and past experiences, has made a great deal of information available. Tourists can access this information to support their decision making process. This information is freely accessible online and generates so-called “open data”. While many studies have investigated the effect of online reviews on tourists' decisions, none have directly investigated the extent to which open data analyses might predict tourists' response to a certain destination. To this end, our study contributes to the process of predicting tourists' future preferences via MathematicaTM, software that analyzes a large set of the open data (i.e. tourists’ reviews) that is freely available on tripadvisor. This is devised by generating the classification function and the best model for predicting the destination tourists would potentially select. The implications for the tourist industry are discussed in terms of research and practice.

Suggested Citation

  • Pantano, Eleonora & Priporas, Constantinos-Vasilios & Stylos, Nikolaos, 2017. "‘You will like it!’ using open data to predict tourists' response to a tourist attraction," Tourism Management, Elsevier, vol. 60(C), pages 430-438.
    • Handle: RePEc:eee:touman:v:60:y:2017:i:c:p:430-438
    DOI: 10.1016/j.tourman.2016.12.020
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    Cited by:

    1. Ben Haobin Ye & Huiyue Ye & Rob Law, 2020. "Systematic Review of Smart Tourism Research," Sustainability, MDPI, vol. 12(8), pages 1-15, April.
    2. Yuejiao Wang & Shiwei Shen & Marios Sotiriadis & Li Zhang, 2020. "Suggesting a Framework for Performance Evaluation of Tourist Attractions: A Balance Score Approach," Sustainability, MDPI, vol. 12(15), pages 1-22, August.
    3. Tarmo Kalvet & Maarja Olesk & Marek Tiits & Janika Raun, 2020. "Innovative Tools for Tourism and Cultural Tourism Impact Assessment," Sustainability, MDPI, vol. 12(18), pages 1-30, September.
    4. Giglio, Simona & Pantano, Eleonora & Bilotta, Eleonora & Melewar, T.C., 2020. "Branding luxury hotels: Evidence from the analysis of consumers’ “big” visual data on TripAdvisor," Journal of Business Research, Elsevier, vol. 119(C), pages 495-501.
    5. Josef Zelenka & Tracy Azubuike & Martina Pásková, 2021. "Trust Model for Online Reviews of Tourism Services and Evaluation of Destinations," Administrative Sciences, MDPI, vol. 11(2), pages 1-21, March.
    6. Estela Marine-Roig, 2017. "Measuring Destination Image through Travel Reviews in Search Engines," Sustainability, MDPI, vol. 9(8), pages 1-18, August.
    7. Qian Yao & Yong Shi & Hai Li & Jiahong Wen & Jianchao Xi & Qingwei Wang, 2020. "Understanding the Tourists’ Spatio-Temporal Behavior Using Open GPS Trajectory Data: A Case Study of Yuanmingyuan Park (Beijing, China)," Sustainability, MDPI, vol. 13(1), pages 1-13, December.
    8. A Fronzetti Colladon & B Guardabascio & R Innarella, 2021. "Using social network and semantic analysis to analyze online travel forums and forecast tourism demand," Papers 2105.07727, arXiv.org.
    9. Hernández, Juan M. & Kirilenko, Andrei P. & Stepchenkova, Svetlana, 2018. "Network approach to tourist segmentation via user generated content," Annals of Tourism Research, Elsevier, vol. 73(C), pages 35-47.
    10. Giuseppe Giordano & Ilaria Primerano & Pierluigi Vitale, 2021. "A Network-Based Indicator of Travelers Performativity on Instagram," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 631-649, August.
    11. Chi Yunxian & Li Renjie & Zhao Shuliang & Guo Fenghua, 2020. "Measuring multi-spatiotemporal scale tourist destination popularity based on text granular computing," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-33, April.
    12. Richard Fedorko, 2021. "Gender Differences in the Perception of Selected Aspectsof Social Media as Part of Ecommerce Activities during a Pandemic," GATR Journals jmmr286, Global Academy of Training and Research (GATR) Enterprise.
    13. Michela Fazzolari & Marinella Petrocchi, 2018. "A study on online travel reviews through intelligent data analysis," Information Technology & Tourism, Springer, vol. 20(1), pages 37-58, December.
    14. Marie Al-Ghossein & Talel Abdessalem & Anthony Barré, 2018. "Open data in the hotel industry: leveraging forthcoming events for hotel recommendation," Information Technology & Tourism, Springer, vol. 20(1), pages 191-216, December.
    15. Boley, B. Bynum & Jordan, Evan J. & Kline, Carol & Knollenberg, Whitney, 2018. "Social return and intent to travel," Tourism Management, Elsevier, vol. 64(C), pages 119-128.

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