Semester of Graduation
Spring 2019
Degree
Master of Science (MS)
Department
Environmental Science
Document Type
Thesis
Abstract
Disaster Resilience is the capacity of a community to ‘bounce back’ from disastrous events. Most studies rely on traditional data such as census data to study community resilience. With the advent of social media era, the new data source gives us an opportunity to explore the application of Twitter data to better understand disaster resilience. A research question is: does Twitter use correlate with disaster resilience? In other words, will communities with more Twitter users be more resilient to disasters, presumably because they are more likely to be better informed? The underlying issue is that if there are social and geographical disparities in Twitter use patterns, how will such disparities affect communities’ disaster resilience?
This study examined if there is a relationship between Twitter use and community resilience during Hurricane Isaac, which hit Louisiana and Mississippi in August 2012. First, the thesis applied the Resilience Inference Measurement (RIM) model to calculate the resilience indices of 146 counties. Second, Twitter data during the three weeks of Hurricane Isaac were examined to see if there are significant geographical and social disparities in Twitter use through the three main phases of emergency management (Preparedness, Response, Recovery). Third, correlation analyses were conducted to test if twitter use pattern can be used to predict disaster resilience.
The results show that communities with higher socioeconomic conditions tend to have more twitter activities, communities with higher exposure to hazard tend to have more twitter activities. There are significant positive correlation between community resilience indices and twitter activities.
Recommended Citation
Wang, Kejin, "TWITTER USE IN HURRICANE ISAAC AND ITS IMPLICATIONS TO DISASTER RESILIENCE" (2019). LSU Master's Theses. 4876.
https://repository.lsu.edu/gradschool_theses/4876
Committee Chair
Lam Nina
DOI
10.31390/gradschool_theses.4876
Included in
Environmental Studies Commons, Geographic Information Sciences Commons, Spatial Science Commons