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Text Mining Tweets on Post-COVID-19 Sustainable Tourism: A Social Media Network and Sentiment Analysis

In: COVID-19, Tourist Destinations and Prospects for Recovery

Author

Listed:
  • Dongdong Wu

    (College of Tourism and Service Management, Nankai University)

  • Hui Li

    (College of Tourism and Service Management, Nankai University)

  • Yueqing Li

    (Department of Industrial and Systems Engineering, Lamar University)

  • Yuhong Wang

    (School of Business, Jiangnan University)

Abstract

The primary purpose of this chapter is to get to know the public attitude towards sustainable tourism after COVID-19 and its polarity or emotion. Using Twitter Archiving Google Sheet, 6718 tweets were collected from July 11 to August 10, 2021, with the hashtags #covid19 and #tourism, #sustainabletourism or #ecotourism or #responsibletourism. Tableau and Gephi were used to visualise and aggregate the social media network. Using R Studio, the word frequency, association and sentiment analysis were carried out. The main findings are as follows: (1) retweets take most of all data; (2) media accounts are more visible and active than individual ones in the community network; (3) the “trust” emotion and “anticipation” emotion are dominant in the tweets. Besides, this chapter also tried to use related social behaviour theories to explain the observed social media user behaviours. Practical implications have also been provided to dissolve people’s psychological and emotional problems and enhance people’s confidence in tourism recovery.

Suggested Citation

  • Dongdong Wu & Hui Li & Yueqing Li & Yuhong Wang, 2023. "Text Mining Tweets on Post-COVID-19 Sustainable Tourism: A Social Media Network and Sentiment Analysis," Springer Books, in: Kaitano Dube & Godwell Nhamo & MP Swart (ed.), COVID-19, Tourist Destinations and Prospects for Recovery, chapter 0, pages 261-276, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-22257-3_14
    DOI: 10.1007/978-3-031-22257-3_14
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