Changes in public travel willingness in the post-COVID-19 era: Evidence from social network data

Yazao Yang; Haodong Tang; Tangzheng Weng; Yazao Yang; Haodong Tang; Tangzheng Weng

doi:10.3934/era.2023187

Electronic Research Archive

2023, Volume 31, Issue 7: 3688-3703. doi: 10.3934/era.2023187

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Research article

Changes in public travel willingness in the post-COVID-19 era: Evidence from social network data

School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China

Received: 26 February 2023 Revised: 11 April 2023 Accepted: 19 April 2023 Published: 26 April 2023

Amid the impact of COVID-19, the public's willingness to travel has changed, which has had a fundamental impact on the ridership of urban public transport. Usually, travel willingness is mainly analyzed by questionnaire survey, but it needs to reflect the accurate psychological perception of the public entirely. Based on Weibo text data, this paper used natural language processing technology to quantify the public's willingness to travel in the post-COVID-19 era. First, web crawler technology was used to collect microblog text data, which will discuss COVID-19 and travel at the same time. Then, based on the Naive Bayes classification algorithm, travel sentiment analysis was carried out on the data, and the relationship between public travel willingness and urban public transport ridership was analyzed by Spearman correlation analysis. Finally, the LDA topic model was used to conduct content topic research on microblog text data during and after COVID-19. The results showed that the mean values of compelling travel emotion were -0.8197 and -0.0640 during and after COVID-19, respectively. The willingness of the public to travel directly affects the ridership of urban public transport. Compared with the COVID-19 period, the public's fear of travel infection in the post-COVID-19 era has significantly improved, but it still exists. The public pays more attention to the level of COVID-19 prevention and control and the length of travel time on public transport.
- urban traffic,
- travel emotion,
- LDA topic model,
- naive bayes,
- text categorization
Citation: Yazao Yang, Haodong Tang, Tangzheng Weng. Changes in public travel willingness in the post-COVID-19 era: Evidence from social network data[J]. Electronic Research Archive, 2023, 31(7): 3688-3703. doi: 10.3934/era.2023187

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Abstract

Amid the impact of COVID-19, the public's willingness to travel has changed, which has had a fundamental impact on the ridership of urban public transport. Usually, travel willingness is mainly analyzed by questionnaire survey, but it needs to reflect the accurate psychological perception of the public entirely. Based on Weibo text data, this paper used natural language processing technology to quantify the public's willingness to travel in the post-COVID-19 era. First, web crawler technology was used to collect microblog text data, which will discuss COVID-19 and travel at the same time. Then, based on the Naive Bayes classification algorithm, travel sentiment analysis was carried out on the data, and the relationship between public travel willingness and urban public transport ridership was analyzed by Spearman correlation analysis. Finally, the LDA topic model was used to conduct content topic research on microblog text data during and after COVID-19. The results showed that the mean values of compelling travel emotion were -0.8197 and -0.0640 during and after COVID-19, respectively. The willingness of the public to travel directly affects the ridership of urban public transport. Compared with the COVID-19 period, the public's fear of travel infection in the post-COVID-19 era has significantly improved, but it still exists. The public pays more attention to the level of COVID-19 prevention and control and the length of travel time on public transport.

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