Leveraging geotagged Twitter data to examine neighborhood happiness, diet, and physical activity

被引:52
作者
Nguyen, Quynh C. [1 ]
Kath, Suraj [2 ]
Meng, Hsien-Wen [1 ]
Li, Dapeng [3 ]
Smith, Ken R. [4 ]
VanDerslice, James A. [5 ]
Wen, Ming [6 ]
Li, Feifei [2 ]
机构
[1] Univ Utah, Coll Hlth, Dept Hlth Promot & Educ, 1901 E South Campus Dr,Annex B 2124, Salt Lake City, UT 84112 USA
[2] Univ Utah, Sch Comp, 1901 E South Campus Dr,Annex B 2124, Salt Lake City, UT 84112 USA
[3] Univ Utah, Dept Geog, 1901 E South Campus Dr,Annex B 2124, Salt Lake City, UT 84112 USA
[4] Univ Utah, Dept Family & Consumer Studies, 1901 E South Campus Dr,Annex B 2124, Salt Lake City, UT 84112 USA
[5] Univ Utah, Sch Med, Dept Family & Prevent Med, Div Publ Hlth, 1901 E South Campus Dr,Annex B 2124, Salt Lake City, UT 84112 USA
[6] Univ Utah, Dept Sociol, 1901 E South Campus Dr,Annex B 2124, Salt Lake City, UT 84112 USA
基金
美国国家科学基金会;
关键词
Twitter messaging; Neighborhood; Happiness; Physical activity; Diet; Food; BODY-MASS INDEX; BUILT ENVIRONMENT; FOOD; OBESITY; MORTALITY; INCOME; SEGREGATION; MULTILEVEL; HEALTH; PREVALENCE;
D O I
10.1016/j.apgeog.2016.06.003
中图分类号
P9 [自然地理学]; K9 [地理];
学科分类号
0705 ; 070501 ;
摘要
Objectives: Using publicly available, geotagged Twitter data, we created neighborhood indicators for happiness, food and physical activity for three large counties: Salt Lake, San Francisco and New York. Methods: We utilize 2.8 million tweets collected between February August 2015 in our analysis. Geocoordinates of where tweets were sent allow us to spatially join them to 2010 census tract locations. We implemented quality control checks and tested associations between Twitter-derived variables and sociodemographic characteristics. Results: For a random subset of tweets, manually labeled tweets and algorithm labeled tweets had excellent levels of agreement: 73% for happiness; 83% for food, and 85% for physical activity. Happy tweets, healthy food references, and physical activity references were less frequent in census tracts with greater economic disadvantage and higher proportions of racial/ethnic minorities and youths. Conclusions: Social media can be leveraged to provide greater understanding of the well-being and health behaviors of communities-information that has been previously difficult and expensive to obtain consistently across geographies. More open access neighborhood data can enable better design of programs and policies addressing social determinants of health. (C) 2016 Published by Elsevier Ltd.
引用
收藏
页码:77 / 88
页数:12
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