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Job Satisfaction Through the Lens of Social Media: Rural--Urban Patterns in the U.S

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  • Stefano M Iacus
  • Giuseppe Porro

Abstract

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.

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  • Stefano M Iacus & Giuseppe Porro, 2025. "Job Satisfaction Through the Lens of Social Media: Rural--Urban Patterns in the U.S," Papers 2512.05144, arXiv.org.
    • Handle: RePEc:arx:papers:2512.05144
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    References listed on IDEAS

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    3. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
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