Climate-related natural disasters such as floods, droughts, wildfires, and heat waves are expected to worsen as the Earth’s warming trend continues, stressing communities all across the country. Understanding the resilience of a community facing a climate-related crisis event is critical to improving its adaptive capacity to future disasters.
A new algorithm developed by graduate student Benjamin Rachunok analyzes individuals’ tweets to better understand how they respond to crises, offering a new way to inform decisions on disaster management. The technique looks at individuals’ tweets associated with an event and breaks them down into categories of community resilience they define as ecological, economical, institutional, social, infrastructure and quality of life. The algorithm automatically calculates and generates a heat map of the fingerprint, which is the specific combination of categories that make up individuals’ responses to an event. The heat map makes it easier to see which aspects of community resilience are most evident in people’s reactions to certain crises, as well as how they relate to each other. A comparison of the fingerprints between events show that major disasters such as hurricanes and earthquakes have a unique resilience fingerprint which is similar among different events of the same type (e.g., Hurricane Harvey and Hurricane Irma).
Rachunok used funding from a PCCRC student travel grant to present his findings at the 2019 Institute for Industrial & Systems Engineers Annual Conference.