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

Engineering notes

Engineering notes will be added by the aipentium editorial team.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为大语言模型、生成式AI、ChatGPT相关技术、计算机视觉、深度学习等高价值论文补充中文说明。

Original abstract

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.

Links and sources

Comments