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Tourism demand forecasting with online news data mining

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  • Park, Eunhye
  • Park, Jinah
  • Hu, Mingming

Abstract

This study empirically tests the role of news discourse in forecasting tourist arrivals by examining Hong Kong. It employs structural topic modeling to identify key topics and their meanings related to tourism demand. The impact of the extracted news topics on tourist arrivals is then examined to forecast tourism demand using the seasonal autoregressive integrated moving average with the selected news topic variables method. This study confirms that including news data significantly improves forecasting performance. Our forecasting model using news topics also outperformed the others when the destination was experiencing social unrest at the local level. These findings contribute to tourism demand forecasting research by incorporating discourse analysis and can help tourism destinations address various externalities related to news media.

Suggested Citation

  • Park, Eunhye & Park, Jinah & Hu, Mingming, 2021. "Tourism demand forecasting with online news data mining," Annals of Tourism Research, Elsevier, vol. 90(C).
    • Handle: RePEc:eee:anture:v:90:y:2021:i:c:s0160738321001511
    DOI: 10.1016/j.annals.2021.103273
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    1. Ulrich Gunter & Irem Önder & Stefan Gindl, 2019. "Exploring the predictive ability of LIKES of posts on the Facebook pages of four major city DMOs in Austria," Tourism Economics, , vol. 25(3), pages 375-401, May.
    2. Victoria Cramer & Svenn Torgersen & Einar Kringlen, 2004. "Quality of Life in a City: The Effect of Population Density," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 69(1), pages 103-116, October.
    3. Li, Hengyun & Hu, Mingming & Li, Gang, 2020. "Forecasting tourism demand with multisource big data," Annals of Tourism Research, Elsevier, vol. 83(C).
    4. Qiu, Richard T.R. & Wu, Doris Chenguang & Dropsy, Vincent & Petit, Sylvain & Pratt, Stephen & Ohe, Yasuo, 2021. "Visitor arrivals forecasts amid COVID-19: A perspective from the Asia and Pacific team," Annals of Tourism Research, Elsevier, vol. 88(C).
    5. Yu, Qionglei & McManus, Richard & Yen, Dorothy A. & Li, Xiang (Robert), 2020. "Tourism boycotts and animosity: A study of seven events," Annals of Tourism Research, Elsevier, vol. 80(C).
    6. Law, Rob & Li, Gang & Fong, Davis Ka Chio & Han, Xin, 2019. "Tourism demand forecasting: A deep learning approach," Annals of Tourism Research, Elsevier, vol. 75(C), pages 410-423.
    7. Fazito, Mozart & Scott, Mark & Russell, Paula, 2016. "The dynamics of tourism discourses and policy in Brazil," Annals of Tourism Research, Elsevier, vol. 57(C), pages 1-17.
    8. Margaret E. Roberts & Brandon M. Stewart & Edoardo M. Airoldi, 2016. "A Model of Text for Experimentation in the Social Sciences," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 988-1003, July.
    9. Ritchie, Brent W. & Jiang, Yawei, 2019. "A review of research on tourism risk, crisis and disaster management: Launching the annals of tourism research curated collection on tourism risk, crisis and disaster management," Annals of Tourism Research, Elsevier, vol. 79(C).
    10. Shapiro, Adam Hale & Sudhof, Moritz & Wilson, Daniel J., 2022. "Measuring news sentiment," Journal of Econometrics, Elsevier, vol. 228(2), pages 221-243.
    11. Qiu, Richard T.R. & Park, Jinah & Li, ShiNa & Song, Haiyan, 2020. "Social costs of tourism during the COVID-19 pandemic," Annals of Tourism Research, Elsevier, vol. 84(C).
    12. Ardia, David & Bluteau, Keven & Boudt, Kris, 2019. "Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1370-1386.
    13. Kursa, Miron B. & Rudnicki, Witold R., 2010. "Feature Selection with the Boruta Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i11).
    14. Mingming Hu & Haiyan Song, 2020. "Data source combination for tourism demand forecasting," Tourism Economics, , vol. 26(7), pages 1248-1265, November.
    15. Li, Gang & Law, Rob & Vu, Huy Quan & Rong, Jia & Zhao, Xinyuan (Roy), 2015. "Identifying emerging hotel preferences using Emerging Pattern Mining technique," Tourism Management, Elsevier, vol. 46(C), pages 311-321.
    16. Yang, Xin & Pan, Bing & Evans, James A. & Lv, Benfu, 2015. "Forecasting Chinese tourist volume with search engine data," Tourism Management, Elsevier, vol. 46(C), pages 386-397.
    17. Takayuki Morimoto & Yoshinori Kawasaki, 2017. "Forecasting Financial Market Volatility Using a Dynamic Topic Model," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 24(3), pages 149-167, September.
    18. Dehler-Holland, Joris & Schumacher, Kira & Fichtner, Wolf, 2021. "Topic Modeling Uncovers Shifts in Media Framing of the German Renewable Energy Act," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 2(1).
    19. Tobback, Ellen & Naudts, Hans & Daelemans, Walter & Junqué de Fortuny, Enric & Martens, David, 2018. "Belgian economic policy uncertainty index: Improvement through text mining," International Journal of Forecasting, Elsevier, vol. 34(2), pages 355-365.
    20. Song, Haiyan & Qiu, Richard T.R. & Park, Jinah, 2019. "A review of research on tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 75(C), pages 338-362.
    21. Yingfei He & Guoliang Zhang & Lijuan Chen, 2020. "Analysis of News Coverage of Haze in China in the Context of Sustainable Development: The Case of China Daily," Sustainability, MDPI, vol. 12(1), pages 1-15, January.
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    3. Dong Zhang & Pengkun Wu & Chong Wu & Eric W. T. Ngai, 2024. "Forecasting duty-free shopping demand with multisource data: a deep learning approach," Annals of Operations Research, Springer, vol. 339(1), pages 861-887, August.
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    5. Mohamed M. Mostafa, 2023. "A one-hundred-year structural topic modeling analysis of the knowledge structure of international management research," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3905-3935, August.
    6. Raniah Alsahafi & Ahmed Alzahrani & Rashid Mehmood, 2023. "Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations," Sustainability, MDPI, vol. 15(5), pages 1-64, February.
    7. Ruochen Yang & Kun Liu & Chang Su & Shiro Takeda & Junhua Zhang & Shuhao Liu, 2023. "Quantitative Analysis of Seasonality and the Impact of COVID-19 on Tourists’ Use of Urban Green Space in Okinawa: An ARIMA Modeling Approach Using Web Review Data," Land, MDPI, vol. 12(5), pages 1-25, May.
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    10. Li, Xin & Xu, Yechi & Law, Rob & Wang, Shouyang, 2024. "Enhancing tourism demand forecasting with a transformer-based framework," Annals of Tourism Research, Elsevier, vol. 107(C).

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