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Can Twitter be used to predict county excessive alcohol consumption rates?
Brenda Curtis1, Salvatore Giorgi2, Anneke E K Buffone2
1Center on Continuum of Care in Addictions, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
Plos One
|April 5, 2018
Summary
Researchers analyzed Twitter data to predict excessive alcohol consumption rates. Social media language effectively forecasts public health concerns, offering insights beyond traditional demographic factors.
Area of Science:
- Public Health
- Computational Social Science
- Digital Epidemiology
Background:
- Excessive alcohol consumption is a significant public health issue.
- Sociodemographic factors are traditionally used to understand alcohol consumption patterns.
- The potential of social media data for public health surveillance remains underexplored.
Purpose of the Study:
- To determine if excessive alcohol consumption rates can be predicted using Twitter data.
- To investigate if language patterns on Twitter correlate with county-level alcohol consumption.
- To explore the relationship between social media language, socioeconomic status, and excessive drinking.
Main Methods:
- Analysis of over 138 million county-level tweets from 1,384 US counties.
- Application of predictive modeling techniques to identify correlations.
- Utilizing differential and mediating language analysis to understand linguistic patterns.
Main Results:
- Twitter language data accurately predicts excessive alcohol consumption rates.
- Social media language captures consumption patterns beyond sociodemographic factors.
- Mediation analysis revealed that specific Twitter topics explain variance between socioeconomic status and excessive drinking.
Conclusions:
- Twitter data serves as a valuable tool for predicting public health concerns like excessive drinking.
- Integrating predictive modeling with mediation analysis enhances understanding of socioeconomic influences on health behaviors.
- Digital communication platforms offer novel avenues for public health research and intervention.
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