  With the outbreak of the COVID-19 pandemic in 2020, most colleges and
universities move to restrict campus activities, reduce indoor gatherings and
move instruction online. These changes required that students adapt and alter
their daily routines accordingly. To investigate patterns associated with these
behavioral changes, we collected smartphone sensing data using the Beiwe
platform from two groups of undergraduate students at a major North American
university, one from January to March of 2020 (74 participants), the other from
May to August (52 participants), to observe the differences in students' daily
life patterns before and after the start of the pandemic. In this paper, we
focus on the mobility patterns evidenced by GPS signal tracking from the
students' smartphones and report findings using several analytical methods
including principal component analysis, circadian rhythm analysis, and
predictive modeling of perceived sadness levels using mobility-based digital
metrics. Our findings suggest that compared to the pre-COVID group, students in
the mid-COVID group generally (1) registered a greater amount of midday
movement than movement in the morning (8-10am) and in the evening (7-9pm), as
opposed to the other way around; (2) exhibited significantly less intradaily
variability in their daily movement, and (3) had a significant lower
correlation between their mobility patterns and negative mood.
