Understanding public opinion in different disaster stages: a case study of Hurricane Irma

Zhan Xu (Northern Arizona University, Flagstaff, Arizona, USA)
Kenneth Lachlan (University of Connecticut, Hartford, Connecticut, USA)
Lauren Ellis (Northern Arizona University, Flagstaff, Arizona, USA)
Adam Michael Rainear (West Chester University of Pennsylvania, West Chester, Pennsylvania, USA)

Internet Research

ISSN: 1066-2243

Publication date: 27 September 2019



Social media, such as Twitter, has become the first and the most frequent place to visit in order to gain information and establish situational awareness in emergencies and disasters. The purpose of this paper is to examine public opinion on Twitter in different disaster stages using the case of Hurricane Irma.


More than 3.5m tweets capturing the entire disaster lifecycle were collected and analyzed. Topic modeling was used to generate topics at each disaster stage based on Fink’s (1986) four-stage model of crisis and disaster: prodromal, acute, chronic and termination stages.


The results revealed that media reliance varied across different stages. All topics in the prodromal stage were associated with the early warning and real-time news. The topic of lessons learned from Hurricane Harvey was the most popular at this stage. The acute stage recorded the highest number of daily tweets. The most popular topic was the safety of people and animals. In the chronic stage too, the safety of people and animals remained a major concern. Heroic and anti-social behaviors also received substantial attention. In the termination stage, climate change was the most frequently discussed topic. Politics-related discussions were heated.


The results extended and enhanced the four-stage model of crisis and disaster. These findings can help government agencies and crisis managers address audience needs effectively at various crisis stages in a timely manner.



Xu, Z., Lachlan, K., Ellis, L. and Rainear, A. (2019), "Understanding public opinion in different disaster stages: a case study of Hurricane Irma", Internet Research, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/INTR-12-2018-0517

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