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Data-Driven Content Analysis of Social Media: A Systematic Overview of Automated Methods

  • University of Pennsylvania

Research output: Contribution to journalArticlepeer-review

161 Scopus citations

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 languageEnglish
Pages (from-to)78-94
Number of pages17
JournalAnnals of the American Academy of Political and Social Science
Volume659
Issue number1
DOIs
StatePublished - May 15 2015

Keywords

  • content analysis
  • Facebook
  • social media
  • text mining
  • Twitter

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