Future-Oriented Tweets Predict Lower County-Level HIV Prevalence in the United States
OBJECTIVE:
Future
orientation promotes health and well-being at the individual level.
Computerized text analysis of a dataset encompassing billions of words used
across the United States on Twitter tested whether community-level rates of
future-oriented messages correlated with lower human immunodeficiency virus (HIV) rates and moderated the association between
behavioral risk indicators and HIV.
METHOD:
Over 150
million tweets mapped to U.S. counties were analyzed using 2 methods of text
analysis. First, county-level HIV rates
(cases per 100,000) were regressed on aggregate usage of future-oriented
language (e.g., will, gonna). A second data-driven method regressed HIV rates on individual words and phrases.
RESULTS:
Results
showed that counties with higher rates of future tense on Twitter had fewer HIV cases, independent of strong structural
predictors of HIV such
as population density. Future-oriented messages also appeared to buffer health
risk: Sexually transmitted infection rates and references to risky behavior on
Twitter were associated with higher HIV prevalence
in all counties except those with high rates of future orientation. Data-driven
analyses likewise showed that words and phrases referencing the future (e.g.,
tomorrow, would be) correlated with lower HIV prevalence.
CONCLUSION:
Integrating
big data approaches to text analysis and epidemiology with psychological theory
may provide an inexpensive, real-time method of anticipating outbreaks of HIV and etiologically similar diseases.
- 1Department of Psychological Sciences, Texas Tech University.
- 2Department of Psychology, University of Pennsylvania.
- 3Annenberg School for Communication, University of Pennsylvania.
- 4Psychology Department, University of Illinois at Urbana-Champaign.
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