Interest-based and Ideological Biases in Online Content Consumption: Problems and Solutions

This Stanford seminar explores the critical issues of interest-based and ideological biases in online content consumption, examining both problems and potential solutions. Professor Magdalena Wojcieszak from UC Davis presents four research projects that combine computer science methodologies with large-scale human subjects research. Learn about a sock puppet-based audit of YouTube's algorithmic biases, discover why interest-based biases may be more democratically consequential than ideological ones, and explore computational interventions designed to encourage exposure to quality and diverse news content. The presentation addresses pressing democratic threats including populism, polarization, misinformation, and examines the role of social media platforms and recommendation algorithms in these challenges. Professor Wojcieszak, an accomplished researcher with publications in prestigious journals like Science and PNAS, shares valuable insights from her work as director of the ERC Starting Grant EXPO and her involvement with the U.S. 2020 Facebook & Instagram Election Study.