Monitoring the well-being of vulnerable transit riders using machine learning based sentiment analysis and social media: Lessons from COVID-19 | Zendy

Martino Tran | Zendy; Christina Draeger | Zendy; Xuerou Wang | Zendy; Abbas Nikbakht | Zendy

Open Access

Monitoring the well-being of vulnerable transit riders using machine learning based sentiment analysis and social media: Lessons from COVID-19

Author(s) -

Martino Tran,

Christina Draeger,

Xuerou Wang,

Abbas Nikbakht

Publication year - 2022

Publication title -

environment and planning b urban analytics and city science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.889

H-Index - 90

eISSN - 2399-8091

pISSN - 2399-8083

DOI - 10.1177/23998083221104489

Subject(s) - social distance , public transport , pandemic , data collection , population , transit (satellite) , social media , public health , business , mass gathering , ethnic group , psychology , covid-19 , advertising , geography , applied psychology , public relations , political science , environmental health , transport engineering , medicine , sociology , engineering , social science , nursing , disease , pathology , law , infectious disease (medical specialty)

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