They found that combining known physical and social risk factors, including income, education, smoking, diabetes, hypertension, obesity, race and marital status, accounted for about 35% of heart disease mortality within a county. However, language used on Twitter alone accounted for about 42% of heart disease mortality within a county. Combining Twitter language and known risk factors accounted for about 43% of heart disease mortality risk. This suggests that language used on Twitter is an important indicator of health outcomes. But what were these people saying on Twitter that predicted heart disease in their county?
The research team identified 3 categories of language use that specifically predicted increased risk for heart disease mortality in their county: aggression & hostility, interpersonal tension, and disengagement. Anger and hostility was a category comprised of frequent use of expletives. Interpersonal tension was a category comprised of frequent use of words such as “hate,” “jealous,” “fake,” and “drama,” not to mention some more expletives. Finally, disengagement was a category comprised of frequent use of words related to boredom and fatigue. Each of these categories was a significant predictor of increased heart disease mortality in a county.
There were also three other categories. These categories were Skilled Occupations, with words referring to attending conferences, learning, and meeting new people; Positive Experiences, using words that refer to friends, weekends, food, company, and things described as wonderful and fantastic; and finally Optimism, which reflects the use of words reflecting possibilities, achievements, father, goals, success, strength, and courage. Frequency of Twitter content in each of these 3 categories was protective against heart disease risk in counties.
But what does this mean? Saying bad words on Twitter causes you to die of heart disease? Posting angry, hostile tweets causes your neighbors to die of heart disease?
Because this research is cross-sectional, these are just correlations, not causes of heart disease. It’s possible that pre-existing heart disease causes people to be more hostile, angry and pessimistic. In that case, language patterns on social media may be an early sign of undiagnosed heart disease that is an area for future preventive science to explore. It’s also possible that engaging with the world with more anger, hostility, and pessimism causes physiological changes to the body that lead to heart disease. Since we know that stress causes heart disease, this pathway is extremely plausible. However, the people who die of heart disease tend to be older, while the people on Twitter tend to be younger. The people in this study that were tweeting expletives were not the ones dying that year, so there’s something much greater reflected in these findings than what predicts heart disease within an individual.
We all live in communities, big and small. Other people matter, but more importantly, your behavior matters in the lives of other people.
Eichstaedt, J. C., Schwartz, H. A., Kern, M. L., Park, G., Labarthe, D. R., Merchant, R. M., ... & Seligman, M. E. (2015). Psychological language on twitter predicts county-level heart disease mortality. Psychological science,26(2), 159-169.