Abstract:

American democracy has been undermined by an “infodemic” of fake news, coupled with the widespread segregation of consumers into ideologically homogenous echo chambers by inscrutable algorithms deployed by rapacious social media platforms—or so we are told. In this talk, I will critically examine claims of this sort—made frequently by politicians, journalists, and public intellectuals—summarizing several recent papers that leverage large-scale representative panel data for US media consumption. Contrary to conventional wisdom, I argue that fake news is relatively rare, echo chambers on television are much larger and stickier than their online equivalents, and individual preferences dominate algorithmic filtering in determining consumption patterns. I further argue that it is trivially easy to mislead people without resorting to outright falsehoods and that researchers should accordingly pay more attention to biased information, even when it is factually accurate. I conclude by introducing the media bias detector, a recently launched project of Penn’s Computational Social Science Lab, that seeks to characterize and expose bias in mainstream media.

Zoom Link: https://upenn.zoom.us/j/94075987313