Psychological language on Twitter predicts county-level heart disease mortality.

ABSTRACT: Hostility and chronic stress are known risk factors for heart disease, but they are costly to assess on a large scale. We used language expressed on Twitter to characterize community-level psychological correlates of age-adjusted mortality from atherosclerotic heart disease (AHD). Language patterns reflecting negative social relationships, disengagement, and negative emotions-especially anger-emerged as risk factors; positive emotions and psychological engagement emerged as protective factors. Most correlations remained significant after controlling for income and education. A cross-sectional regression model based only on Twitter language predicted AHD mortality significantly better than did a model that combined 10 common demographic, socioeconomic, and health risk factors, including smo

SUBMITTER: Eichstaedt JC 

PROVIDER: S-EPMC4433545 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature