Changing or unchanging Chinese attitudes toward ride-hailing? A social media analytics perspective from 2018 to 2021

Long Chen, Jiahui Huang, Peng Jing, Bichen Wang, Xiaozhou Yu, Ye Zha and Chengxi Jiang

Transportation Research Part A: Policy and Practice, 2023, vol. 178, issue C

Abstract: Despite the global popularity of ride-hailing services, frequent events in recent years have caused the public to query and even refuse to adopt ride-hailing. The public’s attitudes are the decisive factor affecting ride-hailing development. Previous studies identified the public’s attitude toward ride-hailing at a one-time point through questionnaire design without monitoring changes in the public’s attitude. This study aims to analyze the evolution and reasons for the public’s attitudes toward ride-hailing in terms of trend lines and significant events. We collected 114,361 comments across social media platforms (Sina Weibo and Tik Tok) on Chinese ride-hailing events from May 2018 to September 2021. Through sentiment analysis to investigate the evolution of the public’s attitudes toward ride-hailing, we identified four significant events that led to significant changes in public attitudes. We then employed Latent Dirichlet Allocation (LDA) topic model and text network analysis to examine the comments in these significant events to understand the exact reasons for the change in attitudes. The results indicate that the public’s attitude variations are closely linked with social events. Meanwhile, among all topics, Platform and Safety are constant public concerns. Other topics (e.g., Publicity, Government, and Pity) of public concern are related to significant events. The gap between perceived and actual security toward ride-hailing services seems to exist. We also found gender discrimination against females in ride-hailing events. The findings provide valuable insights into the future development of ride-hailing.

Keywords: Ride-hailing; Public comments; Evolution; Significant events; Latent Dirichlet Allocation topic model; Text network analysis (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (3)

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DOI: 10.1016/j.tra.2023.103881

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