A model to measure tourist preference toward scenic spots based on social media data: A case of Dapeng in China

Yao Sun, Hang Ma, Hon Wan Edwin Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

16 Citations (Scopus)


Research on tourist preference toward different tourism destinations has been a hot topic for decades in the field of tourism development. Tourist preference is mostly measured with small group opinion-based methods through introducing indicator systems in previous studies. In the digital age, e-tourism makes it possible to collect huge volumes of social data produced by tourists from the internet, to establish a new way of measuring tourist preference toward a close group of tourism destinations. This paper introduces a new model using social media data to quantitatively measure the market trend of a group of scenic spots from the angle of tourists' demand, using three attributes: tourist sentiment orientation, present tourist market shares, and potential tourist awareness. Through data mining, cleaning, and analyzing with the framework of Machine Learning, the relative tourist preference toward 34 scenic spots closely located in the Dapeng Peninsula is calculated. The results not only provide a reliable "A-rating" system to gauge the popularity of different scenic spots, but also contribute an innovative measuring model to support scenic spots planning and policy making in the regional context.
Original languageEnglish
Article number43
JournalSustainability (Switzerland)
Issue number1
Publication statusPublished - 26 Dec 2017


  • Measuring model
  • Scenic spots planning
  • Social media data
  • Tourism destinations
  • Tourist preference

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Management, Monitoring, Policy and Law

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