Surveying the Use of Social Media Data and Natural Language Processing Techniques to Investigate Natural Disasters-Reference-Cited by-同舟云学术

Surveying the Use of Social Media Data and Natural Language Processing Techniques to Investigate Natural Disasters

Published:2024-11 Issue:4 Volume:25 Page:
ISSN:1527-6988
Container-title:Natural Hazards Review
language:en
Short-container-title:Nat. Hazards Rev.

Author:

Ma Zihui¹,Li Lingyao²,Mao Yujie³,Wang Yu⁴^ORCID,Patsy Olivia Grace⁵,Bensi Michelle T.⁶^ORCID,Hemphill Libby⁷,Baecher Gregory B.⁸^ORCID

Affiliation:

1. Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park, MD 20742.

2. Postdoctoral, School of Information, Univ. of Michigan, Ann Arbor, MI 48109.

3. Ph.D. Candidate, Center for Technology and Systems Management, Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park, MD 20742.

4. Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park, MD 20742. ORCID: .

5. Researcher, Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park, MD 20742.

6. Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park, MD 20742 (corresponding author). ORCID: .

7. Associate Professor, School of information, Univ. of Michigan, Ann Arbor, MI 48109.

8. Professor, Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park, MD 20742. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/NHREFO.NHENG-2047

Reference189 articles.

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3. Automatic detection of passable roads after floods in remote sensed and social media data

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5. Alam F. S. Joty and M. Imran. 2018. “Graph based semi-supervised learning with convolution neural networks to classify crisis related tweets.” In Proc. Int. AAAI Conf. on Web and Social Media. Washington DC: Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/icwsm.v12i1.15047.