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

机译:基于大规模推特数据分析的Covid-19大流行对乘车服务的影响

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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.
机译:近年来,乘车服务已经受到普及,因为诸如降低旅行成本,交通拥堵和排放等属性。 然而,随着Covid-19的影响,估计乘车海平市场估计失去其公平份额作为交通模式。 在正常和批判的情况下,乘车服务的服务用户通过在诸如Twitter等社交平台上发布来表达他们的担忧,习惯和情感。 因此,推特作为新兴数据源是一个有效而创新的数字平台,可以观察骑车者在乘车服务中的行为。 本研究保湿了与共同流动相关的大规模推特反应,对比较情绪和情感分析进行了解,以了解Covid-19对大流行前和大流行条件的运输网络服务的影响。 在大流行,与“悲伤”(15%)和“愤怒”(15%)相关的负推文(34%)最普遍存在数据集中。

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