Data-driven Computational Social Science

DD-CSS is an effort to build new computational tools to help collect and analyze social media data. It is powered by Flask, a highly modular microframework for Python, to encourage other developers to contribute to this project.

There is a growing interest in mining the social web by so many professions for different purposes. So, while many parties may benefit from DD-CSS, our primary target is computational social scientists. We would like you to import your collection & analysis methods into DD-CSS especially if you are publishing in social computing conferences.



  • Obtain an OAuth access token on behalf of a Twitter user
  • Get the friends/followers list of a user as JSON/CSV file
  • Get last 3200 tweets of a user in JSON/CSV format


  • Obtain an OAuth access token on behalf of a Facebook user
  • Get the number of shares of a url



  • db.queries.ensureIndex({username:1, created_time:1, qname:1})
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