Correlating Twitter Use with Disaster Resilience at Two Spatial Scales: A Case Study of Hurricane Sandy

ABSTRACT

Disaster resilience describes the ability of a community to bounce back from disaster impacts by resilience building activities. Social media provides an innovative way to observe human attitudes and responses, especially during disasters. However, most previous social media and disasters studies were conducted at a coarse spatial scale such as by county. This study analyzes Twitter activities during Hurricane Sandy in 2012, at the county and the zip code area levels in the five affected states. The study examines two questions: (1) will the relationships between disparities in social media use and disparities in disaster resilience found at the county level in previous studies still hold at the zip code area level? And (2) what new information or patterns can be revealed with the zip code area level analysis? Results show that correlations between Twitter use indices and social-environmental variables representing community resilience found at the county level in previous studies still hold, but they are weaker at the zip code area level. The study also shows that zip code areas that have major transportation hubs and commercial activities or low night-time population are major factors affecting Twitter use indices and hence the correlations. Future research should consider adding data on land use types and population dynamics to help improve social media use for disaster resilience analysis. Furthermore, employing a multiscale analysis approach can reduce uncertainties involved in analysis and obtain a more thorough understanding of the relationships between Twitter use and geographical and socioeconomic characteristics of the affected communities.

KEYWORDS:

• Disaster resilience
• Hurricane Sandy
• social media
• sentiment analysis
• spatial scale

Acknowledgements

We acknowledge Mongo database, Python, and its open-source packages for the creation of programming code for Twitter data processing. We also would like to thank all the anonymous reviewers for their comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

Samples of the Twitter data during Hurricane Sandy can be accessed at the LSU Interdisciplinary Computation & Analysis of Resilience (ICAR) website: https://icar.lsu.edu/datasets/index.html.

Additional information

Funding

This research is supported by the U.S. National Science Foundation under The Interdisciplinary Behavioral and Social Science Research (IBSS) Program [Award No. 1620451] and the Rapid Response Research (RAPID) Program [Award No. 1762600]. Any opinions, findings, and conclusions or recommendations expressed in this article are those of the authors and do not necessarily reflect the views of the funding agency.