Identifying the role of media discourse in tourism demand forecasting

Yihong Chen, Tao Hu and Peiying Song

Current Issues in Tourism, 2024, vol. 27, issue 3, 413-427

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.

Date: 2024
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/13683500.2023.2165050 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:rcitxx:v:27:y:2024:i:3:p:413-427

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/rcit20

DOI: 10.1080/13683500.2023.2165050

Access Statistics for this article

Current Issues in Tourism is currently edited by Jennifer Tunstall

More articles in Current Issues in Tourism from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().