title: 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 smoking, diabetes, hypertension, and obesity. Capturing community psychological characteristics through social media is feasible, and these characteristics are strong markers of cardiovascular mortality at the community level.
authors.affiliation: Department of Psychology, University of Pennsylvania johannes.penn@gmail.com jeich@sas.upenn.edu andy.schwartz@gmail.com.
authors.forename: Johannes C
authors.initials: JC
authors.lastname: Eichstaedt
authors.affiliation: Department of Psychology, University of Pennsylvania Department of Computer and Information Science, University of Pennsylvania.
authors.forename: Hansen Andrew
authors.initials: HA
authors.lastname: Schwartz
authors.affiliation: Department of Psychology, University of Pennsylvania Graduate School of Education, University of Melbourne.
authors.forename: Margaret L
authors.initials: ML
authors.lastname: Kern
authors.affiliation: Department of Psychology, University of Pennsylvania.
authors.forename: Gregory
authors.initials: G
authors.lastname: Park
authors.affiliation: School of Medicine, Northwestern University.
authors.forename: Darwin R
authors.initials: DR
authors.lastname: Labarthe
authors.affiliation: Department of Emergency Medicine, University of Pennsylvania.
authors.forename: Raina M
authors.initials: RM
authors.lastname: Merchant
authors.affiliation: Department of Computer and Information Science, University of Pennsylvania.
authors.forename: Sneha
authors.initials: S
authors.lastname: Jha
authors.affiliation: Department of Computer and Information Science, University of Pennsylvania.
authors.forename: Megha
authors.initials: M
authors.lastname: Agrawal
authors.affiliation: Department of Psychology, University of Pennsylvania.
authors.forename: Lukasz A
authors.initials: LA
authors.lastname: Dziurzynski
authors.affiliation: Department of Psychology, University of Pennsylvania.
authors.forename: Maarten
authors.initials: M
authors.lastname: Sap
authors.affiliation: Department of Psychology, University of Pennsylvania.
authors.forename: Christopher
authors.initials: C
authors.lastname: Weeg
authors.affiliation: Department of Psychology, University of Pennsylvania.
authors.forename: Emily E
authors.initials: EE
authors.lastname: Larson
authors.affiliation: Department of Psychology, University of Pennsylvania Department of Computer and Information Science, University of Pennsylvania.
authors.forename: Lyle H
authors.initials: LH
authors.lastname: Ungar
authors.affiliation: Department of Psychology, University of Pennsylvania.
authors.forename: Martin E P
authors.initials: ME
authors.lastname: Seligman
mesh_terms: D003324:Coronary Artery Disease / Q000401:mortality* / Q000523:psychology*; D003430:Cross-Sectional Studies; D003625:Data Collection / Q000706:statistics & numerical data; D004644:Emotions; D005260:Female; D006801:Humans; D007802:Language; D008297:Male; D008960:Models, Psychological; D015233:Models, Statistical; D012044:Regression Analysis; D012307:Risk Factors; D061108:Social Media / Q000706:statistics & numerical data*; D014481:United States / Q000453:epidemiology
keywords: big data; emotions; heart disease; language; open data; open materials; risk factors; social media; well-being