The Impact of COVID-19 Confinement on Regional Mobility of Spatial-Temporal Social Networks

Abstract

Over the past few months, COVID-19 has emerged to the world as a new threat to humanity and communities, expanding from a few small infected cities to hundreds of countries around the world impacting businesses, education, economics, and almost every activity associated with human life. This had led many researchers and scientists to analyze and study different factors and variables that obtain timely information on the outbreak of COVID-19. One of the main factors that helped in spreading the corona-virus is human mobility. Since detailed information about human movement during outbreaks are difficult to obtain, social networks comes as an alternative with its massive volume of publicly available data. In this research, we propose mobility detection and identification of social media's spatio-temporal data, as a proxy for human mobility. We aim to discover and explore an in-depth level of mobility data extracted from social media applications to uncover the relation between COVID-19 spread and daily mobility ratio in Kuwait regional area. With the use of the latest mobility data extracted from Twitter users, we have shown that user mobility is linked to the positive cases of COVID-19, with a relatively high correlation coefficient. Moreover, we have analyzed and discussed how the impact of COVID-19 affected user behavior and mobility habits.