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Wildfires and social media discourse: exploring mental health and emotional wellbeing through Twitter.
García, Yury E; Villa-Pérez, Miryam Elizabeth; Li, Kuang; Tai, Xiao Hui; Trejo, Luis A; Daza-Torres, Maria L; Montesinos-López, J Cricelio; Nuño, Miriam.
Afiliação
  • García YE; Department of Public Health Sciences, University of California, Davis, Davis, CA, United States.
  • Villa-Pérez ME; School of Engineering and Sciences, Tecnologico de Monterrey, Atizapán de Zaragoza, Mexico.
  • Li K; Department of Public Health Sciences, University of California, Davis, Davis, CA, United States.
  • Tai XH; Department of Statistics, University of California, Davis, Davis, CA, United States.
  • Trejo LA; School of Engineering and Sciences, Tecnologico de Monterrey, Atizapán de Zaragoza, Mexico.
  • Daza-Torres ML; Department of Public Health Sciences, University of California, Davis, Davis, CA, United States.
  • Montesinos-López JC; Department of Public Health Sciences, University of California, Davis, Davis, CA, United States.
  • Nuño M; Department of Public Health Sciences, University of California, Davis, Davis, CA, United States.
Front Public Health ; 12: 1349609, 2024.
Article em En | MEDLINE | ID: mdl-38680934
ABSTRACT

Introduction:

The rise in global temperatures due to climate change has escalated the frequency and intensity of wildfires worldwide. Beyond their direct impact on physical health, these wildfires can significantly impact mental health. Conventional mental health studies predominantly rely on surveys, often constrained by limited sample sizes, high costs, and time constraints. As a result, there is an increasing interest in accessing social media data to study the effects of wildfires on mental health.

Methods:

In this study, we focused on Twitter users affected by the California Tubbs Fire in 2017 to extract data signals related to emotional well-being and mental health. Our analysis aimed to investigate tweets posted during the Tubbs Fire disaster to gain deeper insights into their impact on individuals. Data were collected from October 8 to October 31, 2017, encompassing the peak activity period. Various analytical methods were employed to explore word usage, sentiment, temporal patterns of word occurrence, and emerging topics associated with the unfolding crisis.

Results:

The findings show increased user engagement on wildfire-related Tweets, particularly during nighttime and early morning, especially at the onset of wildfire incidents. Subsequent exploration of emotional categories using Linguistic Inquiry and Word Count (LIWC) revealed a substantial presence of negative emotions at 43.0%, juxtaposed with simultaneous positivity in 23.1% of tweets. This dual emotional expression suggests a nuanced and complex landscape, unveiling concerns and community support within conversations. Stress concerns were notably expressed in 36.3% of the tweets. The main discussion topics were air quality, emotional exhaustion, and criticism of the president's response to the wildfire emergency.

Discussion:

Social media data, particularly the data collected from Twitter during wildfires, provides an opportunity to evaluate the psychological impact on affected communities immediately. This data can be used by public health authorities to launch targeted media campaigns in areas and hours where users are more active. Such campaigns can raise awareness about mental health during disasters and connect individuals with relevant resources. The effectiveness of these campaigns can be enhanced by tailoring outreach efforts based on prevalent issues highlighted by users. This ensures that individuals receive prompt support and mitigates the psychological impacts of wildfire disasters.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Saúde Mental / Incêndios Florestais / Mídias Sociais Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Saúde Mental / Incêndios Florestais / Mídias Sociais Idioma: En Ano de publicação: 2024 Tipo de documento: Article