Internet Searches for Affect-Related Terms: An Indicator of Subjective Well-Being and Predictor of Health Outcomes across US States and Metro Areas.

BACKGROUND: The present study explored the potential for internet search data to serve as indicators of subjective well-being (SWB) and predictors of health at the state and metro area levels. We propose that searches for positive and negative affect-related terms represent information-seeking behavior of individuals who are experiencing emotions and seeking information about them.

METHOD: Data on the frequency of Google searches for 15 affect terms were collected from Google's Trends website (trends.google.com). These were paired with data on health, self-reported emotions, psychological well-being, personality, and Twitter postings at the state and metro area levels.

RESULTS: Several internet search scores correlated with indicators of cardiovascular health and depression. Some search term scores also correlated strongly with self-reported emotions, well-being metrics, neuroticism, per capita income, and Twitter postings at the state or metro area level. Multiple regression analyses suggest that affect searches predict depression rates at the metro area level beyond the effects of income and other well-being measures.

CONCLUSION: The results highlight the promise and challenges of using internet search data at the aggregate level for physical and mental health assessment and surveillance.