Community Resilience Assessment
The public’s responses to sudden power outages offer valuable insights into a community’s ability to adapt and recover from crises. In this project, we proposed a framework to analyze sentiment and behavioral patterns, assessing community resilience during the 2019 New York City blackout. Through the identification of six distinct behavioral types (including “seek information,” “adjust schedules,” “find shelter,” “enjoy the situation,” “engage in altruistic acts,” and “report incidents”), we introduced an index to track shifts in public responses over time. Our analysis of these trending indexes revealed that New York City residents rapidly adjusted their routines, suggesting a robust community resilience in the face of the power outage. This study not only advances the methodologies employed in emergency management research but also contributes to our understanding of community resilience during emergency events.
Article
Lingyao Li, Zihui Ma, Tao Cao. “Leveraging social media data to study the community resilience of New York City to 2019 power outage.” International Journal of Disaster Risk Reduction.
Power outages across the world have severe social impacts. The public’s responses to power outages provide valuable insights into their capacities of adapting crisis and an invaluable perspective to demonstrate community resilience. As social media has connected people in the community, the discussion on social media can reflect their responses as a criterion of resilience throughout power outages in a timely and effective manner. In the field of power outages, the potentials of social media data have only been investigated with recent advancements of big data techniques. Nonetheless, studies focusing on community resilience using social media data are quite limited. We filled this gap by introducing a novel and quantitative method to study the community resilience throughout power outages, based on a case study on the Manhattan blackout occurred in July 2019. The study examined community resilience from both mental and behavioral perspectives via sentiment analysis and behavior analysis. The sentiment analysis was used to track people’s mental outlook and shape the overall mental status during and after this emergency. On the other side, six major patterns of behaviors were identified, and the behavioral index was defined to learn how the community responded to power outages amid the response and recovery periods. Both the mental and behavioral results reveal that New York City recovered at approximately one and a half hours after the blackout occurred, implying a strong community resilience to such short and emergent power outage events.