We analyze a novel large-scale social-media-based measure of U.S. job satisfaction, constructed by applying a fine-tuned large language model to 2.6 billion georeferenced tweets, and link it to county-level labor market conditions (2013-2023). Logistic regressions show that rural counties consistently report lower job satisfaction sentiment than urban ones, but this gap decreases under tight labor markets. In contrast to widening rural-urban income disparities, perceived job quality converges when unemployment is low, suggesting that labor market slack, not income alone, drives spatial inequality in subjective work-related well-being.

翻译：我们分析了一种基于社交媒体的大规模美国工作满意度度量新方法，该方法通过将微调后的大语言模型应用于26亿条地理标记的推文构建而成，并将其与县级劳动力市场状况（2013-2023年）相关联。逻辑回归分析表明，农村县的工作满意度情感始终低于城市县，但在劳动力市场紧张时这一差距会缩小。与不断扩大的城乡收入差距相反，当失业率较低时，感知的工作质量趋于收敛，这表明劳动力市场松弛度（而非单纯收入）是驱动主观工作相关幸福感空间不平等的主要因素。