  In today's interconnected world of widespread mobility, ubiquitous social
interaction, and rapid information dissemination, the demand for individuals to
swiftly adapt their behaviors has increased dramatically. Timely
decision-making faces new challenges due to the necessity of using finely
temporal-resolved anonymised individual data to keep up with fast-paced
behavioural changes. To tackle this issue, we propose a general framework that
leverages privacy-enhanced GPS data from mobile devices alongside census
information to infer the employment status of individuals over time. By
analysing the mobility patterns of employed and unemployed individuals, we
unveil significant differences in behaviours between the two groups, showing a
contraction in visited locations and a general decline in the exploratory
behaviour of unemployed individuals. Remarkably, these differences intensify
over time since job loss, particularly affecting individuals from more
vulnerable demographic groups. These findings highlight the importance of early
monitoring of unemployed individuals who may face enduring levels of distress.
Overall, our findings shed light on the dynamics of employment-related
behaviour, emphasizing the importance of implementing timely interventions to
support the unemployed and vulnerable populations.
