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

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

PLOS ONE, 2013, vol. 8, issue 5, 1-15

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.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0064417

DOI: 10.1371/journal.pone.0064417

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