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Online social networks are increasingly central in shaping our political opinions. These are also prime spaces where humans co-exist with AI: algorithms to personalize contents and provide recommendations are pervasive in online platforms. Link recommendation algorithms (also known as social recommendation systems) are used to recommend new connections — e.g., friends or users to follow — based on supposed familiarity, similar interests, or the potential to serve as a source of useful information. These algorithms impact the evolution of social networks’ topology, yet their long-term impact on human social dynamics remains hard to evaluate. In this talk, I will present and discuss a model to study such impacts and explore 1) how algorithmic link recommendations interplay with opinion dynamics and 2) the long-term impacts of such algorithms on opinion polarisation. More broadly, I will discuss how algorithmic link recommendations can impact information access and, in turn, affect collective action dynamics.
Fernando P. Santos ( Informatics Institute of the University of Amsterdam)
Assistant Professor
Fernando Santos is an Assistant Professor at the University of Amsterdam. He received his PhD in Computer Science and Engineering in 2018, from Instituto Superior Técnico (Lisbon, Portugal). Fernando’s research lies at the interface of AI and complex systems: He is interested in understanding collective dynamics in multiagent systems and in designing fair/pro-social AI. Before joining UvA, Fernando was a James S. McDonnell postdoctoral fellow at the Department of Ecology and Evolutionary Biology of Princeton University (Levin Lab). He was a visiting student at Princeton, Université Libre de Bruxelles and TU Delft.