人气
2019年冠状病毒病(COVID-19)
社会化媒体
大流行
情绪分析
比例(比率)
愤怒
业务
服务(商务)
广告
2019-20冠状病毒爆发
互联网隐私
营销
计算机科学
万维网
地理
心理学
医学
病理
病毒学
机器学习
传染病(医学专业)
精神科
疾病
爆发
社会心理学
地图学
作者
Syed Ahnaf Morshed,Sifat Shahriar Khan,Raihanul Bari Tanvir,Shafkath Nur
标识
DOI:10.1016/j.jum.2021.03.002
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 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.
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