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Network approach to tourist segmentation via user generated content

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  • Hernández, Juan M.
  • Kirilenko, Andrei P.
  • Stepchenkova, Svetlana

Abstract

The study contributes to the tourism literature by demonstrating an approach to segmenting tourists using network analysis with user-generated content. Online reviews of destination attractions are considered as a proxy for visitation data reflective of tourists’ interests. The connectivity between attractions is represented with a network of links created by tourists visiting and reviewing multiple attractions. Attraction clusters are revealed by segmenting this network using network analysis tools. Two segmentation solutions are provided: a posteriori, in which only review information is taken into account, and mixed, in which tourist groups are defined a priori by their travel interests and age, and this information is combined with visitation information. The findings are validated using geovisualization and by comparing them with randomly simulated models.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:anture:v:73:y:2018:i:c:p:35-47
    DOI: 10.1016/j.annals.2018.09.002
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    References listed on IDEAS

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    1. Liu, Bing & Huang, Songshan (Sam) & Fu, Hui, 2017. "An application of network analysis on tourist attractions: The case of Xinjiang, China," Tourism Management, Elsevier, vol. 58(C), pages 132-141.
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    5. Andrea Lancichinetti & Filippo Radicchi & José J Ramasco & Santo Fortunato, 2011. "Finding Statistically Significant Communities in Networks," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-18, April.
    6. 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.
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    Cited by:

    1. Tomáš Gajdošík, 2020. "Smart tourists as a profiling market segment: Implications for DMOs," Tourism Economics, , vol. 26(6), pages 1042-1062, September.
    2. Humeyra Dogru-Dastan & Svetlana Stepchenkova & Andrei P. Kirilenko, 2022. "Responding to Visitor Density Pre and Post COVID-19 Outbreak: The Impact of Personality Type on Perceived Crowdedness, Feeling of Being Comfortable, and Anticipated Experience," Sustainability, MDPI, vol. 14(7), pages 1-22, March.
    3. Kai Wang & Menghan Wang & Chang Gan & Qinchang Chen & Mihai Voda, 2021. "Tourism Economic Network Structural Characteristics of National Parks in the Central Region of China," Sustainability, MDPI, vol. 13(9), pages 1-19, April.
    4. Kateryna Malinoshevska & Maryna Korzh, 2020. "Marketing Strategies Of Development On The Example Of Green Tourism," Three Seas Economic Journal, Publishing house "Baltija Publishing", vol. 1(2).
    5. Xiaodong Zhang & Haoying Han & Yongjun Tang & Zhilu Chen, 2023. "Spatial Distribution Characteristics and Driving Factors of Tourism Resources in China," Land, MDPI, vol. 12(5), pages 1-16, May.
    6. Egbert Van der Zee & Dario Bertocchi, 2018. "Finding patterns in urban tourist behaviour: a social network analysis approach based on TripAdvisor reviews," Information Technology & Tourism, Springer, vol. 20(1), pages 153-180, December.

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