PLoS ONE· 2013Q1
The Geography of Happiness: Connecting Twitter Sentiment and Expression, Demographics, and Objective Characteristics of Place
- 522citations
- Q1SCImago
- 2013year
Short summary
Twitter sentiment and word choice correlate with US state and city demographics, health, and happiness levels, with social media potentially estimating real-time population-scale measures like obesity rates.
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Key points
- Combined 80 million geo-tagged Twitter words (2011) with state/urban characteristics.
- Generated taxonomies of states/cities based on word use similarities.
- Estimated happiness levels for states and cities.
- Correlated demographics with happiness and word choice with urban characteristics (e.g., education, obesity).
AI-generated from the title and abstract; the full text is not read.
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.
The authors' abstract, as published at the source. PLoS ONE, 2013 · DOI ↗
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Field: Transportation
TransportationSocial Sciences