  The outbreak of COVID-19 highlights the need for a more harmonized, less
privacy-concerning, easily accessible approach to monitoring the human mobility
that has been proved to be associated with the viral transmission. In this
study, we analyzed 587 million tweets worldwide to see how global collaborative
efforts in reducing human mobility are reflected from the user-generated
information at the global, country, and the U.S. state scale. Considering the
multifaceted nature of mobility, we propose two types of distance: the
single-day distance and the cross-day distance. To quantify the responsiveness
in certain geographical regions, we further propose a mobility-based responsive
index (MRI) that captures the overall degree of mobility changes within a time
window. The results suggest that mobility patterns obtained from Twitter data
are amendable to quantitatively reflect the mobility dynamics. Globally, the
proposed two distances had greatly deviated from their baselines after March
11, 2020, when WHO declared COVID-19 as a pandemic. The considerably less
periodicity after the declaration suggests that the protection measures have
obviously affected people's travel routines. The country scale comparisons
reveal the discrepancies in responsiveness, evidenced by the contrasting
mobility patterns in different epidemic phases. We find that the triggers of
mobility changes correspond well with the national announcements of mitigation
measures. In the U.S., the influence of the COVID-19 pandemic on mobility is
distinct. However, the impacts varied substantially among states. The strong
mobility recovering momentum is further fueled by the Black Lives Matter
protests, potentially fostering the second wave of infections in the U.S.
