Pathways in Network Science - A seminar with Roberta Sinatra

Quantifying Political Polarization on a Network Using Generalized Euclidean Distance

Keynote to: Science of Science for Data Scientists

Program: Welcoming talk: The many faces of Fake News, by session chair, Luca Rossi NLP, Fake News and Social Media Scientific Talk: NLP and social media, Marina Charquero Ballestar, Postdoc, AU Scientific Talk: Editorial media and social media platforms: it’s complicated, Aske Kammer, RUC Business Talk: Daniel Hanse, tjekdet.dk Business Talk: Complexities of tacking the […]

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

Bicycle networks: From data quality assessment to computational analysis Cycling is marginalized despite being a promising solution towards sustainable transport. In parallel, cycling data and cycling research are also marginalized, posing many opportunities for improvement and open questions. Here, we first present our cycling data quality tool which enables intrinsic and extrinsic assessment and reporting […]