Abstract
Researchers have long measured people’s thoughts, feelings, and personalities using carefully designed survey questions, which are often given to a relatively small number of volunteers. The proliferation of social media, such as Twitter and Facebook, offers alternative measurement approaches: automatic content coding at unprecedented scales and the statistical power to do open-vocabulary exploratory analysis. We describe a range of automatic and partially automatic content analysis techniques and illustrate how their use on social media generates insights into subjective well-being, health, gender differences, and personality.
| Original language | English |
|---|---|
| Pages (from-to) | 78-94 |
| Number of pages | 17 |
| Journal | Annals of the American Academy of Political and Social Science |
| Volume | 659 |
| Issue number | 1 |
| DOIs | |
| State | Published - May 15 2015 |
Keywords
- content analysis
- social media
- text mining
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