Revealing Disaster Resilience Inequalities during Texas 2021 Winter Storm through Geospatial Data Mining

External stressors, such as pandemics and natural disasters have been demonstrated to cause adverse social impacts on human communities, including infrastructure disruption, emotional distress, etc. The literature has suggested that these stressors' adverse impacts fall disproportionately on disadvantaged populations, leading to changing levels of community resilience inequalities. The Covid-19 pandemic and lockdown/social distancing policies, compounded by the Texas Winter Storm in early 2021, have caused tremendous infrastructural damages and disruptions to social networks and various degrees of mental stress and depression among different populations in Texas communities. As communities recover from the physical damages, mental health restoration also requires urgent policy and research attention. Therefore, monitoring subjective well-being across time and space and initiating actions to assist the restoration of happiness is critical for the recovery of communities and the long-term equity and resilience of society. In this study, we integrated multiple sources of geospatial data, such as SafeGraph mobility data, Twitter data, winter storm event data to reveal the spatial and temporal disparities of community responses to the event. By integrating socioeconomic factors, human behavior data, and events data, we tried to identify the least resilient communities and the underlying reasons and arguments behind low community resilience under external stressors.