Impact of COVID-19 pandemic on ride-hailing services based on large-scale Twitter data analysis
Autor: | Sifat Shahriar Khan, Raihanul Bari Tanvir, Syed Ahnaf Morshed, Shafkath Nur |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Urbanization. City and country
Public Administration Coronavirus disease 2019 (COVID-19) Shared mobility TNC media_common.quotation_subject Twitter data Geography Planning and Development Internet privacy 0211 other engineering and technologies 02 engineering and technology 010501 environmental sciences Anger 01 natural sciences Ride-hailing Sentiment analysis JF20-2112 Pandemic ddc:710 0105 earth and related environmental sciences media_common Data source Emotion detection business.industry COVID-19 021107 urban & regional planning Popularity Urban Studies Traffic congestion Scale (social sciences) HT361-384 Political institutions and public administration (General) business |
Zdroj: | Journal of Urban Management, Vol 10, Iss 2, Pp 155-165 (2021) |
ISSN: | 2226-5856 |
Popis: | 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. |
Databáze: | OpenAIRE |
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