Big Data During Crisis: Lessons from Hurricane Irene
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2015-03-01
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TRIS Online Accession Number:01590525
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Edition:Final Report
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Abstract:The approach taken in this project was to conduct a case study on transportation outages in Hurricane Irene. In this case study, natural language processing (NLP) techniques were used to analyze social media data for transportation outage information. The results of that analysis are then compared with data collected by state transportation agencies using traditional methods to identify whether these outages were identified on social media. The intent of the case study was to characterize the potential of big data from sensor networks to compliment existing sensor networks to create actionable information in a disaster, and to further develop methodologies to analyze these sources of data. Transportation data for Hurricane Irene were collected from the four states of New York, New Jersey, Vermont and New Hampshire, and Twitter data were collected.
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