This week will be focusing on a substantive problem relating to social media and politics. Namely, we will be thinking about so-called “echo chambers” or “filter bubbles.” These refer to platform produced—or algorithmically produced—information environments where the user is exposed only to one sort of political information.
And, normally, this political content is composed of information and opinions agreeable to the user.
Why is this a problem? The argument runs that this is a problem because a healthy society requires citizens to hear, be exposed to, and debate opposing opinions. Without this, societies might become increasingly contentious and polarized.
But how do we study this? And what does computation have to do with it?
Additional reading:
- Bail (2021) (chapters 1-3)
- Fletcher, Robertson, and Nielsen (2021)
Slides
Slides for this week are available here
Bail, Chris. 2021. “Breaking the Social Media Prism.” In. Princeton University Press.
Chen, M. Keith, and Ryne Rohla. 2018.
“The Effect of Partisanship and Political Advertising on Close Family Ties.” Science 360 (6392): 1020–24.
https://doi.org/10.1126/science.aaq1433.
Fletcher, Richard, Craig T. Robertson, and Rasmus Kleis Nielsen. 2021.
“How Many People Live in Politically Partisan Online News Echo Chambers in Different Countries?” Journal of Quantitative Description: Digital Media 1 (August).
https://doi.org/10.51685/jqd.2021.020.
Guess, Andrew M. 2021.
“(Almost) Everything in Moderation: New Evidence on Americans’ Online Media Diets.” American Journal of Political Science 65 (4): 1007–22.
https://doi.org/10.1111/ajps.12589.
Levy, Ro’ee. 2021.
“Social Media, News Consumption, and Polarization: Evidence from a Field Experiment.” American Economic Review 111 (3): 831870.
https://doi.org/10.1257/aer.20191777.