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:
Tue, 04/09/2024 - 20:06
DOI:
10.21227/ea4x-wp41
Data Format:
*.csv (zip)
Research Article Link:
Wildfires and Social Media Discourse: Exploring Mental Health and Emotional Well-Being Through Twitter
License:
Creative Commons Attribution
289 Views
Categories:
Machine Learning
Social Sciences
Keywords:
mental health, well-being, wildfire, twitter dataset, tubbs fire, Natural Language Processing, Sentiment Analysis
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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.

Comments

fire and smoke detection reasearch using deep learning based method.

Submitted by long teng on Thu, 03/21/2024 - 01:30

 I need this datasets

Submitted by zhang mao on Fri, 04/12/2024 - 05:54

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