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Future-oriented tweets predict lower county-level HIV prevalence in the United States
Molly E Ireland1, H Andrew Schwartz2, Qijia Chen3
1Department of Psychological Sciences, Texas Tech University.
Summary
Communities using more future-oriented language on Twitter had lower rates of human immunodeficiency virus (HIV). Future thinking also buffered the link between risky behaviors and HIV, suggesting a public health benefit.
Area of Science:
- Computational social science
- Public health informatics
- Psychological science
Background:
- Future orientation is linked to individual health and well-being.
- Understanding community-level psychological factors can inform public health strategies.
Purpose of the Study:
- To investigate the correlation between community-level future-oriented language on Twitter and human immunodeficiency virus (HIV) rates.
- To determine if future orientation moderates the relationship between behavioral risk factors and HIV prevalence.
Main Methods:
- Analysis of over 150 million geo-tagged tweets from U.S. counties using text analysis.
- Regression models correlating county-level HIV rates with aggregate future-oriented language usage and individual words/phrases.
Main Results:
- Counties with higher rates of future-oriented language on Twitter exhibited lower HIV cases, independent of demographic factors.
- Future-oriented language use moderated the association between sexually transmitted infection rates/risky behavior references and HIV prevalence.
- Data-driven analysis confirmed that future-referencing words correlated with reduced HIV prevalence.
Conclusions:
- Big data text analysis integrated with psychological theory offers a novel approach to predict disease outbreaks.
- This method provides a potentially inexpensive, real-time tool for anticipating HIV and similar disease trends.
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