Last week, we wrote about winners of the latest round of grantees of the Knight Prototype Fund. One of them was Open Gender Tracking, a team that’s working to figure out the best way to automatically analyze gender bias in news outlets, both in terms of who is writing the news, and who the news is being written about. This week, Source gets into the details of how they built the GenderTracker and how it works.

Under the hood, OGT is a ruby application (we use JRuby), which schedules batch jobs to process data from news APIs and static files. Jobs are queued using Redis. Text processing is done with Apache OpenNLP, but it really could be anything. Jobs don’t even have to be written in Ruby.

Outputs can be incredibly diverse. For our Global Voices study, we imported Open Gender Tracker into the R statistical software. The Boston Globe project is more interactive, storing results in MongoDB and serving them out to a Backbone.js app that visualizes the results.

Our new Global Name Data repository is another exciting part of this project. We have collected names from the US, UK, and Ireland and are hoping to add Chinese names from my colleague Huan Sun’s research on gender on Sina Weibo. We’re actively looking for name gender datasets from other cultures and would love to add more to this growing list.