Text mining hurricane harvey tweet data: Lessons learned and policy recommendations

Author:

Ngamassi LouisORCID,Shahriari HesamORCID,Ramakrishnan Thiagarajan,Rahman ShahedurORCID

Funder

Department of Homeland Security

Publisher

Elsevier BV

Subject

Geology,Safety Research,Geotechnical Engineering and Engineering Geology

Reference82 articles.

1. Federal Emergency Management Agency, U.S. Department of Homeland Security, “Houston Strong: Hurricane Harvey Lessons Learned and the Path Forward”, Hearing Before the Homeland Security Committee, U.S. House of Representatives,2018

2. Federal Emergency Management Agency, Historic Disaster Response to Hurricane Harvey in Texas,2017

3. Characterization of Peak Streamflows and Flood Inundation of Selected Areas in Southeastern Texas and Southwestern Louisiana from the August and September 2017 Flood Resulting from Hurricane Harvey;Watson,2018

4. Hurricane Harvey Facts, Damage and Costs;Amadeo,2018

5. Hurricane Harvey Report: A Fact-Finding Effort in the Direct Aftermath of Hurricane Harvey in the Greater Houston Region;Sebastian,2017

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1. Finding public outrage on social media during the Texas energy crisis;Energy Research & Social Science;2024-03

2. How citizens engage with the social media presence of climate authorities: the case of five Brazilian cities;npj Climate Action;2023-12-12

3. Eliciting social themes of flood mitigation and community engagement studies through text mining;International Journal of Building Pathology and Adaptation;2023-09-18

4. A Review Text-based Recommendation System in Text Mining;2022 IEEE International Conference of Computer Science and Information Technology (ICOSNIKOM);2022-10-19

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