Two Americas of Well-Being: Divergent Rural–Urban Patterns of Life Satisfaction and Happiness from 2.6 B Social Media Posts

Abstract

Using 2.6 billion geolocated tweets (2014–2022) and a fine-tuned generative language model, we construct county-level indicators of life satisfaction and happiness for the United States. We document an apparent rural–urban paradox: even in unadjusted county-level means, rural counties express higher life satisfaction while urban counties exhibit greater happiness. This opposite gradient persists and is further characterized once the two are treated as distinct layers of subjective well-being, evaluative vs. hedonic, showing that each maps differently onto place, politics, and time. Democratic-leaning areas show a suggestive negative association with evaluative well-being, conditional on structural and temporal controls, but this effect is modest and does not extend to happiness, where no meaningful partisan gradient emerges. Temporal shocks dominate the hedonic layer: happiness falls sharply during 2020–2022, whereas life satisfaction moves more modestly. These patterns are robust across logistic and OLS specifications with clustered standard errors and align with well-being theory. Interpreted as associations for the population of geolocated tweets, the results show that large-scale, language-based indicators can help clarify why prior findings about the rural–urban divide may differ by distinguishing the type of well-being expressed, offering a transparent, reproducible complement to traditional surveys.