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Profiling Macau cultural tourists by using user-generated content from online social media

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Abstract

The topic of constructing a typology of the cultural tourists visiting a particular destination has interested the professionals since early 1990s. A number of typologies, often quite similar to each other, have been proposed and occasionally evaluated at various destinations. While most of the literature is purely conceptual, some works use typological frameworks to empirically categorize cultural tourists at a particular destination sourcing from survey results, typically by administrating a questionnaire to inbound and outbound travelers. This work, to the contrary, constructs an empirical typology of international cultural tourists who have visited Macau based on their reviews on TripAdvisor. The aim of this work is to discover visitation patterns to the nucleus of Macau’s culture by analyzing user-generated content data using text analysis approaches. This model can automatically indicate the probability of a visitor being one particular culture tourist type. The results of this work will offer insights into local tourism authorities and industries for better resource allocation and cultural tourism promotion.

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  1. http://whc.unesco.org/en/list/?type=natural.

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Acknowledgements

This work is supported by a research grant from the Macau Science and Technology Development Fund (Grant number 081/2014/A).

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Authors and Affiliations

  1. Tourism College, Institute for Tourism Studies, Colina de Mong-Ha, Macau, China

    Shanshan Qi & Cora Un In Wong

  2. Department of Management, Marketing and Entrepreneurship, College of Business and Law, University of Canterbury, Christchurch, New Zealand

    Ning Chen

  3. College of Engineering and Science, Victoria University, Footscray, Australia

    Jia Rong & Jiahua Du

Authors
  1. Shanshan Qi
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  2. Cora Un In Wong
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  3. Ning Chen
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  4. Jia Rong
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  5. Jiahua Du
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Corresponding author

Correspondence to Jia Rong.

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Qi, S., Wong, C.U.I., Chen, N. et al. Profiling Macau cultural tourists by using user-generated content from online social media. Inf Technol Tourism 20, 217–236 (2018). https://doi.org/10.1007/s40558-018-0120-0

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  • DOI: https://doi.org/10.1007/s40558-018-0120-0

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