ABSTRACT
The communication revolution that happened in the last ten years has increased the use of technology in the transportation world. Intelligent Transportation Systems wish to predict how many buses are needed in a transit system. With the pandemic effect that the world has faced since early 2020, it is essential to study the impact of the pandemic on the transit system. This paper proposes the leverage of Internet of Things (IoT) devices to predict the number of bus ridership before and during the pandemic. We compare the collected data from Kobe city, Hyogo, Japan, with data gathered from a college city in Virginia, USA. Our goal is to show the effect of the pandemic on ridership through the year 2020 in two different countries. The ultimate goal is to help transit system managers predict how many buses are needed if another pandemic hits. © 2021 IEEE.
ABSTRACT
This study analyzed Twitter discourse to understand the association of the COVID-19 pandemic with mental health. The study compared tweets' volume over time, tweets' volume per mental health category, emotions, and the top hashtags on mental health before and after November 2019, the month on which the first COVID-19 case was reported. We analyzed a total of 273 million English tweets on mental health collected from 56 million unique users. Results and analysis showed a significant shift in trend for the volume of tweets on mental health over time. There was also a notable increase in the volume of tweets on depression, anxiety, stress, and suicide mental health groups. The volume of tweets posted by males and females was comparable. Finally, there was a noticeable increase in the average daily tweets that mention suicide prevention and mental health during the COVID-19 pandemic. © AMCIS 2021.