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On September 9, 2018, Hurricane Irma swept across south Florida, leaving a path of destruction across the entire state. Miami-Dade County, at the southern tip of the state, avoided a direct hit. However, the storm left the county and its dozens of municipalities with gigantic mounds of storm debris. As the weeks went by, the piles festered and frustration with the pace of the clean-up mounted. Two dump sites in particular drew the attention of media and community activists: a park ringed by single family homes in Liberty City, a black community in the heart of Miami; and historic Virginia Key, the only beach open to black citizens under Jim Crow segregation. This research examines three narratives -- media coverage, official explanations from local governments, and reactions on social media -- as a way to investigate how the dumping of storm debris in black spaces was justified, interrogated, and contested in the aftermath of one of the worst hurricanes to strike Miami-Dade County in over a decade. Climate change models predict the increasing frequency of super storms like Irma, and discussions of how coastal cities respond in terms of infrastructure and resiliency are growing. This investigation looks at two components of this response that have not been as widely considered: what are the institutional and citizen responses in the aftermath of these storms, and how will issues of race and historic geographic marginalization be either acknowledged or ignored as the problems associated with climate change grow ever more acute and pressing.

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.

Microblogging is an important channel used to disseminate online public opinion during an emergency. Analyzing the features and evolution mechanism of online public opinion during an emergency plays a significant role in crisis management.

This paper uses the event of Hurricane Irma and combines it with the life cycle of online public opinion evolution to understand the effect of different types of emotional (joy, anger, sadness, fear, disgust) microblogs (tweets) on information dissemination. The research was performed in the context of Hurricane Irma by using tweets associated with that event.

This paper demonstrates that negative emotional information has a greater communication effect, and further, the target audience that receives more exposure to negative emotional microblogs has a stronger tendency to retweet. Meanwhile, emotions expressed in tweets and the life cycle of public opinion evolution exert interactive effects on the retweeting behavior of the target audience.

For future research, a professional dictionary and the context should be taken into consideration to make the modeling in the text more normative and analyzable.

This paper aims to reveal how the emotions of a tweet affect its virality in terms of diffusion volume in the context of an emergency event.

The conclusion made in this paper can shed light on the real-time regulation and public opinion transmission, as well as for efficient intelligence service and emergency management.

In this study, Hurricane Irma is taken as an example to explore the factors influencing the information dissemination during emergencies on the social media environment. The relationship between the sentiment of a tweet and the life cycle of public opinion and its effect on tweet volume were investigated.

Natural disasters are increasingly more frequent and intense, which makes it critical for emergency managers to engage social media users during crises. This study examined emergency official accounts' social media engagement at each disaster stage based on Fink's four-stage model of crisis and disaster: prodromal, acute, chronic and termination stages and linked topics and sentiments to engagement.

Using text mining and sentiment analysis, 1,226 original tweets posted by 66 major emergency official Twitter accounts and more than 15,000 retweets elicited across the life cycle of Hurricane Irma were analyzed.

Results identified the most engaging official accounts and tweets. Most tweets and the most engaging tweets were posted in the prodromal stage. Tweets related to certain topics were significantly more engaging than others. The most frequently tweeted topics by official accounts were less engaging than some seldom tweeted topics. Negative sentiment words increased the engagingness of the tweet. Sadness was the strongest predictor of tweet engagement. Tweets that contained fewer sadness words were more engaging. Fear was stronger in positively predicting tweet engagement than anger. Results also demonstrated that words for fear and anger were critical in engaging social media discussions in the prodromal stage. Words for sadness made the tweets less engaging in the chronic stage.

This study provided detailed instructions on how to increase the engagingness of emergency management official accounts during disasters using computational methods. Findings have practical implications for both emergency managers and crisis researchers.