Talk Highlight

Bio

Santo Fortunato is the Director of the Indiana University Network Science Institute (IUNI) and a Professor at Luddy School of Informatics, Computing, and Engineering of Indiana University. Previously he was professor of complex systems at the Department of Computer Science of Aalto University, Finland. Prof. Fortunato got his PhD in Theoretical Particle Physics at the University of Bielefeld In Germany. His focus areas are network science, especially community detection in graphs, computational social science and science of science. His research has been published in leading journals, including Nature, Science, Nature Physics, PNAS, Physical Review Letters, Physical Review X, Reviews of Modern Physics, Physics Reports and has collected over 40,000 citations (Google Scholar). His single-author article Community detection in graphs (Physics Reports 486, 75-174, 2010) is one of the best known and most cited papers in network science. Fortunato received the Young Scientist Award for Socio- and Econophysics 2011, a prize given by the German Physical Society, for his outstanding contributions to the physics of social systems. He is Fellow of the Network Science Society (2022) and of the American Physical Society (2022). He is the Founding Chair of the International Conference of Computational Social Science (IC2S2), which he first organized in Helsinki in June 2015. He was Chair of Networks 2021, the largest ever event on network science, a historical merger of the NetSci and Sunbelt conferences. He is author of the book A First Course in Network Science, by Cambridge University Press (2020), the most accessible textbook on the new science of networks.

Abstract

In this talk I will highlight some contributions in my focus research areas: network science and the science of science. We propose a measure based on the concept of robustness, that avoids Newman-Girvan modularity's biases by design: robustness modularity is the probability to find trivial partitions when the structure of the network is randomly perturbed. Also, I will discuss the effectiveness of graph embeddings, specifically node2vec, at discovering community structure. I will also show how an iterative procedure, that alternates embedding and edge weighting, makes clusters more easily detectable.

In the science of science I have focused on the dynamics of impact and the evolution of science. The distributions of citations of papers published in the same discipline and year rescale to a universal curve, by properly normalizing the raw number of cites. Nobel Laureates are an endangered species. Finally I will present evidence of social contagion in science: active authors in a certain field induce their collaborators to work in that field.