Periodic Reporting for period 2 - REBOUND (An algorithmic framework for reducing bias and polarization in online media)
Reporting period: 2021-09-01 to 2023-02-28
In this project we will develop theoretical foundations and a concrete set of algorithmic techniques to address deficiencies in today’s online media. We will develop methods to discover structure and patterns of segregation, conflict, and closeness in social-media systems. We will address the issues of reducing bias and polarization, breaking information silos, and creating awareness of users to explore alternative viewpoints. We will also study the effect of different design features to the willingness of the users to explore viewpoints that conflict their opinion.
The project is structured along three intertwined research thrusts: knowledge discovery, exploration, and content recommendation. To accomplish its aims the project will formulate novel problem representations that provide a deeper understanding of the undesirable phenomena observed in online media and allow for effective remedial actions. Strong emphasis will be given on designing algorithms that are scalable to large data, are able to deal with uncertainty, and offer theoretical guarantees. The end result will be a set of new methods and tools that will contribute to increasing exposure to diverse ideas and improving online deliberation.