01658552

Component

https://doi.org/10.1177/0361198118773896

https://doi.org/10.1177/0361198118773896

Hurricane Sandy was one of the deadliest and costliest of hurricanes of the past few decades. Many states experienced significant power outage; however, many people used social media to communicate while having limited or no access to traditional information sources. Using machine learning techniques, this study explored the evolution of various communication patterns and determined user concerns that emerged over the course of Hurricane Sandy. The original data included ~52M tweets coming from ~13M users between October 14, 2012 and November 12, 2012. A topic model was run on ~763K tweets from the top 4,029 most frequent users who tweeted about Sandy at least 100 times. Some 250 well-defined communication patterns based on perplexity were identified. Conversations of the most frequent and relevant users indicate the evolution of numerous storm-phase (warning, response, and recovery) specific topics. People were also concerned about storm location and time, media coverage, and activities of political leaders and celebrities. Also presented is each relevant keyword that contributed to one particular pattern of user concerns. Such keywords would be particularly meaningful in targeted information-spreading and effective crisis communication in similar major disasters. Each of these words can also be helpful for efficient hash-tagging to reach the target audience as needed via social media. The pattern recognition approach of this study can be used in identifying real-time user needs in future crises.

18-04173

English

pp 125-137

2018

Transportation Research Record: Journal of the Transportation Research Board

Print

Figures (4) ; References (69) ; Tables (3)

Data analysis; Disaster preparedness; Disasters and emergency operations; Hurricanes; Information dissemination; Machine learning; Mass communication; Mathematical models; Networks; Pattern recognition systems; Real time information; Social media

Hurricane Sandy, 2012; Twitter

Data and Information Technology; Planning and Forecasting; Security and Emergencies; Transportation (General)

TRIS, TRB, ATRI

Jan 8 2018 11:01AM

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