Corpus ID: 7143223

Characterizing Geographic Variation in Well-Being Using Tweets

@inproceedings{Schwartz2013CharacterizingGV,
  title={Characterizing Geographic Variation in Well-Being Using Tweets},
  author={H. A. Schwartz and J. Eichstaedt and Margaret L. Kern and Lukasz Dziurzynski and R. E. Lucas and Megha Agrawal and G. Park and S. K. Lakshmikanth and Sneha Jha and M. Seligman and L. Ungar},
  booktitle={ICWSM},
  year={2013}
}
The language used in tweets from 1,300 different US counties was found to be predictive of the subjective well-being of people living in those counties as measured by representative surveys. Topics, sets of co-occurring words derived from the tweets using LDA, improved accuracy in predicting life satisfaction over and above standard demographic and socio-economic controls (age, gender, ethnicity, income, and education). The LDA topics provide a greater behavioural and conceptual resolution into… Expand
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