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Identifying the role of media discourse in tourism demand forecasting

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  • Yihong Chen
  • Tao Hu
  • Peiying Song

Abstract

High-frequency and timely tourism demand forecasting of fine-grained attractions is an effective tool that helps tourism stakeholders make decisions and formulate strategies. However, there are limitations due to the external sensitivity of tourism demand. This research integrated news coverage with other psychosocial variables to comprehensively explore the impact of social unrest on tourism demand. Topic modelling was applied to identify tourism news topics and potential meanings. Sentiment classification was used to convert news into structured data. Sentiment indices and quantities constituted a composite news term. The empirical results showed that the comprehensive inclusion of external elements, especially news coverage, can significantly improve the prediction performance. K-Nearest Neighbour with the news term yielded the best results.

Suggested Citation

  • Yihong Chen & Tao Hu & Peiying Song, 2024. "Identifying the role of media discourse in tourism demand forecasting," Current Issues in Tourism, Taylor & Francis Journals, vol. 27(3), pages 413-427, February.
    • Handle: RePEc:taf:rcitxx:v:27:y:2024:i:3:p:413-427
    DOI: 10.1080/13683500.2023.2165050
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