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

TL;DR

This study analyzes 2.6 billion social media posts to reveal contrasting rural-urban patterns of life satisfaction and happiness in the US, highlighting the importance of distinguishing evaluative and hedonic well-being.

Contribution

It introduces a novel approach using language models to measure and differentiate between evaluative and hedonic well-being at the county level.

Findings

Rural counties show higher life satisfaction, urban counties higher happiness.

Happiness declined sharply during 2020-2022, while life satisfaction remained relatively stable.

Partisan effects on well-being vary by context and type of measure.

Abstract

Using 2.6 billion geolocated social-media posts (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: rural counties express higher life satisfaction while urban counties exhibit greater happiness. We reconcile this by treating the two as distinct layers of subjective well-being, evaluative vs. hedonic, showing that each maps differently onto place, politics, and time. Republican-leaning areas appear more satisfied in evaluative terms, but partisan gaps in happiness largely flatten outside major metros, indicating context-dependent political effects. 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 and align with well-being theory. Interpreted as associations for the population of social-media posts, the results show that large-scale, language-based indicators can resolve conflicting findings about the rural-urban divide by distinguishing the type of well-being expressed, offering a transparent, reproducible complement to traditional surveys.