The issue of information diversity – crucial for healthy democratic debates – has been raised recently due to the widespread use of social media as a source of information. These sharing platforms pose many concerns as the information presented to users is not following a usual editorial process and is often selected by recommender systems. Such algorithms can influence users’ opinions by providing them mostly information aligned with their initial opinions and enclose them in an opinion bubble. In a political context, opinion bubbles can push citizens to adopt more extreme viewpoints and actions than their original inclinations. Polarization was notably shown to generate serious political and public troubles.
BOOM will contribute to political depolarization through novel algorithms that identify and open opinion bubbles. To do this, the project combines expertise and innovations in digital economics, media studies, political science, multimedia data analysis and recommender systems.
The project started in January 2021.