Twitter Tubbs Fire dataset
- Citation Author(s):
-
Yury E. García
(University of California, Davis)
Miryam Elizabeth Villa-Pérez
(Tecnologico de Monterrey)
Kuang Li (University of California, Davis)Xiao Hui Tai (University of California, Davis)Luis A. Trejo
(Tecnologico de Monterrey)
Maria L. Daza–Torres
(University of California, Davis)
J. Cricelio Montesinos-Lopez (University of California, Davis)Miriam Nuño (University of California, Davis) - Submitted by:
- Miryam Villa
- Last updated:
- DOI:
- 10.21227/ea4x-wp41
- Data Format:
- Research Article Link:
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Abstract
Data were collected through the Twitter API, focusing on specific vocabulary related to wildfires, hashtags commonly used during the Tubbs Fire, and terms and hashtags related to mental health, well-being, and physical symptoms associated with smoke and wildfire exposure. We focused exclusively on the period from October 8 to October 31, aligning precisely with the duration of the Tubbs Fire. The final dataset available for analysis consists of 90,759 tweets.
— Dataset usage terms : The use of the data is only for scientific purposes, please provide the corresponding credit to the owners when publishing any work based on this data.
Instructions:
The documentation of the dataset is included in the zip file.
fire and smoke detection reasearch using deep learning based method.
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