October 17, 2017

Breaking your bubble

This is the first part of a two-part series about a class project on online filter bubbles. In this post, we talk about our pedagogical approach and how we carried out the project. To read more about the results of the project, go to Part Two.

By Janet Xu and Matthew J. Salganik

The 2016 US presidential election dramatically increased public attention to online filter bubbles and their impacts on society. These online filter bubbles—roughly, personalized algorithms that over-expose people to information that is consistent with their prior beliefs—are interesting, important, and tricky to study. These three characteristics made online filter bubbles an ideal topic for our undergraduate social network class. In this post, we will describe a multi-week, student-led project on algorithmic filter bubbles that we ran with 130 students. We’ll describe what we did, how it worked, and what we’d do differently next time. You can read about what we learned from the results — which turned out to be pretty surprising — here.

[Read more…]