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Mask images on Twitter increase during COVID-19 mandates, especially in Republican counties
Xiaofeng Lin1, Georgia Kernell2,3, Tim Groeling4
1Department of Statistics, University of California - Los Angeles, Los Angeles, CA, 90024, USA.
Scientific Reports
|December 9, 2022
Summary
Mask mandates increased mask wearing by 20% on average, particularly in Republican-leaning areas. This study used geotagged Twitter images to track public health behavior during the COVID-19 pandemic.
Area of Science:
- Public Health
- Social Science
- Data Science
Background:
- Mask-wearing is crucial for mitigating COVID-19 transmission.
- Measuring real-world mask compliance is challenging but vital for policy.
- Public opinion surveys offer insights but lack continuous, granular data.
Purpose of the Study:
- To develop and validate a novel method for estimating mask-wearing behavior.
- To analyze the impact of mask mandates on mask-wearing at the county level.
- To explore variations in mask-wearing across different political demographics.
Main Methods:
- Utilized geotagged Twitter image data from March-September 2020 in the US.
- Developed an estimation model for mask-wearing from visual data.
- Validated the model using public opinion survey data.
- Conducted county-level analysis of mask-wearing trends.
Main Results:
- A significant positive association was found between mask mandates and mask-wearing.
- Mask mandates were associated with an average 20% increase in mask-wearing.
- The effect of mask mandates on mask-wearing was strongest in Republican-leaning counties.
- Geotagged social media data proved effective for monitoring public health behaviors.
Conclusions:
- Geotagged social media images offer a scalable method for monitoring public health behaviors like mask-wearing.
- Governmental policies, such as mask mandates, demonstrably influence citizen behavior.
- Understanding regional and demographic differences in behavior is key to effective public health crisis management.
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