NEtwoRks, Data, and Society (NERDS)

Quantifying biases and inequalities in science Every day our life is made easier by efficient algorithms that search and rank scientific information. Yet, these algorithms have an issue: they are trained on citation data that is ingrained with human biases. Therefore the output is inherently biased too, creating inequalities, raising concerns of discrimination, and harming […]

Node Vector Distances: Methods and Applications Michele is an associate professor at IT University of Copenhagen since 2020. He mainly works on algorithms for the analysis of complex networks, with methods spanning from Computer Science to physics, and on applying the extracted knowledge to a variety of problems, including economic development, human mobility, and the […]

Estimating Affective Polarization on a Social Network with Michele Coscia

Details TBA