Impact of COVID-19 pandemic on ride-hailing services based on large-scale Twitter data analysis

被引:48
|
作者
Morshed, Syed Ahnaf [1 ]
Khan, Sifat Shahriar [2 ]
Tanvir, Raihanul Bari [3 ]
Nur, Shafkath [4 ]
机构
[1] Florida Int Univ, Dept Civil & Environm Engn, 10555 West Flagler St,EC 3730, Miami, FL 33174 USA
[2] Univ Akron, Dept Elect Engn, Leigh Hall,Room 515, Akron, OH 44325 USA
[3] Florida Int Univ, Sch Comp & Informat Sci, 10555 West Flagler St,EC 3730, Miami, FL 33174 USA
[4] Islamic Univ Technol, Dept Civil & Environm Engn, Gazipur, Bangladesh
关键词
Ride-hailing; TNC; Sentiment analysis; Emotion detection; Twitter data; COVID-19;
D O I
10.1016/j.jum.2021.03.002
中图分类号
TU98 [区域规划、城乡规划];
学科分类号
0814 ; 082803 ; 0833 ;
摘要
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 ridehailing 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 ridehailing 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.
引用
收藏
页码:155 / 165
页数:11
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