Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/86562
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Type: | Journal article |
Title: | The geography of happiness: connecting twitter sentiment and expression, demographics, and objective characteristics of place |
Author: | Mitchell, L. Frank, M. Harris, K. Dodds, P. Danforth, C. |
Citation: | PLoS One, 2013; 8(5):e64417-1-e64417-15 |
Publisher: | Public Library of Science |
Issue Date: | 2013 |
ISSN: | 1932-6203 1932-6203 |
Editor: | Sánchez, A. |
Statement of Responsibility: | 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. |
Keywords: | Humans Cluster Analysis Emotions Happiness Health Status Geography Algorithms Socioeconomic Factors Internet Urban Population United States |
Rights: | © 2013 Mitchell et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
DOI: | 10.1371/journal.pone.0064417 |
Published version: | http://dx.doi.org/10.1371/journal.pone.0064417 |
Appears in Collections: | Aurora harvest 2 Mathematical Sciences publications |
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hdl_86562.pdf | Published version | 3.41 MB | Adobe PDF | View/Open |
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