We use nodes to represent entities and edges to represent interactions or relationships between them. The organisation of such edges into different patterns is related to different phenomena among which assortative mixing, i.e. the tendency of similar nodes to be interconnected. The investigation of assortative mixing, measured via the assortativity coefficient, represents a fundamental aspect for the understanding of networks.
In this talk, after a brief introduction on networks, I will focus on the phenomenon of assortative mixing showing how the assortativity coefficient can be used to get a finer interpretation of real-world networks. In particular, observing how certain social networks (e.g. Facebook) display a narrow range of assortatvity, I'll show how the interplay between network structure and node metadata prohibits interactions among similar nodes.
Joint work with: Leto Peel (UCLouvain), Jean-Charles Delvenne (UCLouvain) and Antonio Iovanella (University of Rome "Tor Vergata")
Bio: Matteo Cinelli is a post-doc researcher at the Institute for Complex Systems of the National Research Council (ISC-CNR). He works on interdisciplinarity topics involving networks with applications that range from industrial engineering to finance. He is currently working on misinformation spreading and fake news detection in online social networks.