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

被引:215
作者
Mitchell, Lewis [1 ,2 ]
Frank, Morgan R. [1 ,2 ]
Harris, Kameron Decker [1 ,2 ,3 ]
Dodds, Peter Sheridan [1 ,2 ]
Danforth, Christopher M. [1 ,2 ]
机构
[1] Univ Vermont, Dept Math & Stat, Computat Story Lab, Vermont Complex Syst Ctr, Burlington, VT 05405 USA
[2] Univ Vermont, Vermont Adv Comp Core, Burlington, VT USA
[3] Univ Washington, Dept Appl Math, Seattle, WA 98195 USA
来源
PLOS ONE | 2013年 / 8卷 / 05期
基金
美国国家科学基金会;
关键词
BODY-MASS-INDEX; OBESITY; POVERTY; GROWTH; LIFE; FAT;
D O I
10.1371/journal.pone.0064417
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:15
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