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Visualizing and Comparing Online Travel Reviews of the Great Walls: A Data Mining Approach

In: Information and Communication Technologies in Tourism 2022

Author

Listed:
  • Jin Ling

    (SIHOM, Woosong University)

  • Nadezda Sorokina

    (SIHOM, Woosong University)

Abstract

This research employs two samples of heritage sites of the Great Wall of China (Ba daling Great Wall and Mu tianyu Great Wall) and their 21000 reviews on TripAdvisor to visualize and induce feature-related comparisons. Word2vec and D3.js are applied for statistical computing and graphing Minimal Spanning Tree (MST) and ThemeRiver. The applications of MST and ThemeRiver are used to delineate outstanding features and clearer feature relationships. In terms of methodology, we applied an innovative research route to combine MST with ThemeRiver to visualize travellers’ online comments. At the same time, the visual results obtained are combined with qualitative analysis to generate valuable, intuitive summaries that can be used for reference in future research. Practically, the results disclose that although both sites are highly enjoyed by tourists, they are significantly different in terms of service, infrastructure and scenery. This article has implications for policymakers and practitioners with regard to making use of online reviews to gather authentic visitor comments on the Great Wall.

Suggested Citation

  • Jin Ling & Nadezda Sorokina, 2022. "Visualizing and Comparing Online Travel Reviews of the Great Walls: A Data Mining Approach," Springer Books, in: Jason L. Stienmetz & Berta Ferrer-Rosell & David Massimo (ed.), Information and Communication Technologies in Tourism 2022, pages 423-427, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-94751-4_39
    DOI: 10.1007/978-3-030-94751-4_39
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