Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/271420 
Year of Publication: 
2021
Citation: 
[Journal:] Journal of Urban Management [ISSN:] 2226-5856 [Volume:] 10 [Issue:] 2 [Year:] 2021 [Pages:] 155-165
Publisher: 
Elsevier, Amsterdam
Abstract: 
Ride-hailing services have gained popularity in recent years due to attributes such as reduced travel costs, traffic congestion, and emissions. However, with the impact of COVID-19, the ride-hailing market is estimated to lose its fair share of an uprising as a transportation mode. During normal and critical circumstances, ride-hailing service users express their concerns, habits, and emotions through posting on social platforms such as Twitter. Hence, Twitter, as an emerging data source, is an effective and innovative digital platform to observe the rider's behavior in ride-hailing services. This study hydrates large-scale Twitter reactions related to shared mobility to perform comparative sentiment and emotion analysis to understand the impact of COVID-19 on transportation network services in pre-pandemic and during pandemic conditions. Amid pandemic, negative tweets (34%) associated with "sad" (15%) and "anger" (15%) emotions were most prevalent in the dataset.
Subjects: 
Ride-hailing
TNC
Sentiment analysis
Emotion detection
Twitter data
COVID-19
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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