RAPID: The Changing Roles of Social Media in Disaster Resilience: The Case of Hurricane Harvey

Louisiana State University, Baton Rouge LA

Investigators

Abstract

Understanding the changing roles and effects of social media use in disaster events, such as Hurricane Harvey in Texas, will help reduce vulnerability and improve resilience of communities to these disaster events. Hurricane Harvey made landfall on August 25, 2017 near Rockport, Texas as a category-4 hurricane. It lingered over the Houston area and dumped over 50-inches of rainfall, causing widespread flooding and damages in the region. This unprecedented disastrous event reveals many issues, including inadequate flood warning and slow response by agencies. At the same time, a new phenomenon emerged during the Harvey event: many residents in the Houston area resorted to social media to call for rescue from flooded homes when the 911 system was overloaded and could not be connected. This changing use of social media marks Harvey as one of the very first disastrous events in which social media have played an important role in facilitating fast-responding rescue missions. The overarching research question is: how effective is social media in enhancing resilience through its new role in response and rescue, and do we see an increase or decrease in the geographical and social disparities of social media use that may have affected the outcome and the resilience of individuals and communities? This project collects time-sensitive Twitter data and online surveys of individuals and organizations in the flood-affected communities in the Houston region so that they can be used to address this key question. The research team collects five types of data including (1) Twitter data during the Harvey event; (2) associated webpages and multimedia embedded in tweets; (3) two time-series online surveys to track residents' sentiment, adaptation strategies, and decisions under uncertainty to stay or leave; (4) online surveys of agencies and residents regarding the new use of Twitter in rescue operations; (5) geographic information layers such as flood maps, damage, and socioeconomic data used to integrate with the others types of data. Methods for mining Twitter data and social network analysis are tested. These first-hand, timely collected data provide information on key concerns, sentiment, and adaptive behavior of individuals and organizations. This is valuable information for decision makers and first responders, thereby supporting efforts to map out better strategies to reduce vulnerability and improve resilience. Results from this project can also be compared with the hurricane events in 2012, thus gaining further insights into whether disparities have increased or decreased and where. From a computational point of view, developing better and more efficient algorithms for mining big data will advance the computation and analysis of resilience. The websites, databases, and reports derived from this project will be available and widely disseminated. The lessons learnt and the methodology used in this project can be utilized to study and compare different disasters in different regions.