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The geography of happiness: connecting twitter sentiment and expression, demographics, and objective characteristics of place

PloS one, 2013-05, Vol.8 (5), p.e64417-e64417 [Peer Reviewed Journal]

COPYRIGHT 2013 Public Library of Science ;2013 Mitchell et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2013 Mitchell et al 2013 Mitchell et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0064417 ;PMID: 23734200

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Title:
The geography of happiness: connecting twitter sentiment and expression, demographics, and objective characteristics of place
Author: Mitchell, Lewis ; Frank, Morgan R ; Harris, Kameron Decker ; Dodds, Peter Sheridan ; Danforth, Christopher M
Sánchez, Angel
Subjects: Algorithms ; Applied mathematics ; Body mass index ; Census of Population ; Cluster Analysis ; Computer Science ; Demographics ; Demography ; Digital media ; Earth Sciences ; Economic growth ; Emotions ; Geography ; Happiness ; Health Status ; Humans ; Internet - classification ; Internet - statistics & numerical data ; Mathematics ; Medicine ; Obesity ; Peace ; Polls & surveys ; Real time ; Researchers ; Social and Behavioral Sciences ; Social networks ; Social organization ; Socioeconomic Factors ; Studies ; Surveys ; Taxonomy ; United States ; Urban areas ; Urban Population - classification ; Urban Population - statistics & numerical data ; Urban populations
Is Part Of: PloS one, 2013-05, Vol.8 (5), p.e64417-e64417
Description: 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.
Publisher: United States: Public Library of Science
Language: English
Identifier: ISSN: 1932-6203
EISSN: 1932-6203
DOI: 10.1371/journal.pone.0064417
PMID: 23734200
Source: Public Library of Science (PLoS) Journals Open Access
GFMER Free Medical Journals
MEDLINE
PubMed Central
ProQuest Central
DOAJ Directory of Open Access Journals

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The geography of happiness: connecting twitter sentiment and expression, demographics, and objective characteristics of place

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