Improving Social Media Geolocation for Disaster Response by Using Text From Images and ChatGPT-Reference-Cited by-同舟云学术

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Improving Social Media Geolocation for Disaster Response by Using Text From Images and ChatGPT

Published:2024-08-21 Issue: Volume: Page:67-72
ISSN:
Container-title:Proceedings of the 2024 11th Multidisciplinary International Social Networks Conference
language:
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Author:

Firmansyah Hafiz Budi¹^ORCID,Lorini Valerio²^ORCID,Mulayim Mehmet Oguz³^ORCID,Gomes Jorge⁴^ORCID,Fernandez-Marquez Jose Luis⁵^ORCID

Affiliation:

1. Université de Geneve, Switzerland and Sumatra Institute of Technology, Indonesia

2. Joint Research Center European Commission, Italy

3. Artificial Intelligence Research Institute, IIIA Spanish National Research Council, Spain

4. Virtual Operations Support Teams VOST Europe, Portugal

5. Université de Geneve, Switzerland

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3675669.3675696

Reference19 articles.

1. Image4Act

2. CrisisMMD: Multimodal Twitter Datasets from Natural Disasters

3. Language independent big-data system for the prediction of user location on Twitter

4. Automatic analysis of social media images to identify disaster type and infer appropriate emergency response

5. Carlo Bono, Barbara Pernici, Mehmet Oguz Mulayim, Jose Luis Fernandez-Marquez, Amudha Ravi Shankar, and Edoardo Nemni. 2022. TriggerCit: Early Flood Alerting using Twitter and Geolocation - a comparison with alternative sources. In 19th ISCRAM Conference.

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