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The Geography of Happiness: Connecting Twitter Sentiment and Expression, Demographics, and Objective Characteristics of Place

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  • Lewis Mitchell
  • Morgan R Frank
  • Kameron Decker Harris
  • Peter Sheridan Dodds
  • Christopher M Danforth

Abstract

We conduct a detailed investigation of correlations between real-time expressions of individuals made across the United States and a wide range of emotional, geographic, demographic, and health characteristics. We do so by combining (1) a massive, geo-tagged data set comprising over 80 million words generated in 2011 on the social network service Twitter and (2) annually-surveyed characteristics of all 50 states and close to 400 urban populations. Among many results, we generate taxonomies of states and cities based on their similarities in word use; estimate the happiness levels of states and cities; correlate highly-resolved demographic characteristics with happiness levels; and connect word choice and message length with urban characteristics such as education levels and obesity rates. Our results show how social media may potentially be used to estimate real-time levels and changes in population-scale measures such as obesity rates.

Suggested Citation

  • Lewis Mitchell & Morgan R Frank & Kameron Decker Harris & Peter Sheridan Dodds & Christopher M Danforth, 2013. "The Geography of Happiness: Connecting Twitter Sentiment and Expression, Demographics, and Objective Characteristics of Place," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-15, May.
    • Handle: RePEc:plo:pone00:0064417
    DOI: 10.1371/journal.pone.0064417
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    References listed on IDEAS

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    1. Andrew J. Oswald & Stephen Wu, 2011. "Well-Being across America," The Review of Economics and Statistics, MIT Press, vol. 93(4), pages 1118-1134, November.
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