Computational Social Listening Lab | UPenn

Twitter Can Predict Rates of Coronary Heart Disease

A Penn study published in Psychological Science found that Twitter language patterns can predict county-level coronary heart disease mortality rates more accurately than traditional risk factors like smoking, income, or diabetes. Expressions of anger, hostility, and stress in tweets were linked to higher heart disease risk, while optimism was protective — demonstrating that community-level language reflects population health. Featured: Lyle Ungar.

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