Financial and economic networks represent a topic of particular interest for network scientists, especially in the post-2007 years. The recent ﬁnancial crisis has, in fact, clearly shown how necessary a paradigm-shift is (from the traditional one based upon the representative agent to a novel, data-driven approach). In this respect, the new attitude has quickly assumed interdisciplinary traits, greatly beneﬁtting from the experimental character of physics, the analytical character of mathematics and the numerical character of computer science.
Reversing the perspective, network theory aims at reconciling theories with observations, by adopting the point of view of statistical physics, i.e. considering ensembles of interacting units (instead of isolated agents) and properties emerging from microscopic dynamics within a probabilistic framework (instead of a simple,deterministic, function optimization).Evaluating the resilience of a financial network to shocks and distresses, quantifying the probability of contagion in an interbank network, individuating early-warning signals of upcoming financial crises and reconstructing missing interbank linkages (in monopartite, bipartite and multiplex networks) are only some of the issues addressed by our group.
The analysis of economic networks, on the other hand, aims at reconciling traditional economic theory with network theory. As an example, one of the issue addressed by our group concerns the interpretation of topological quantities in terms of purely macroeconomic quantities. Let us think about the gravity model, which is defined by the countries GDP and their geographic distances: are the latter informative about the countries connectivity or their degree correlations?
One of the most promising future development of complexity science and network theory is the study of brain. Indeed, understanding the extent to which tools and techniques developed within network theory may help understanding the brain functioning is the aim of our research line.
With the name "natural networks" we refer to both biological and medical networks. In particular, the analysis of the latter represents one of the topics of greater interest for network scientists. The main scientific question of this activity is to discover if network theory can help in modelling biological systems.
Social networks are very popular. However, the way information spreads on them is still unclear. Our research line aims at understanding how people interact on social platforms as Facebook and Twitter, the way opinions are born and shared, the nature of the communities which naturally emerge as a consequence of social interactions.
Life of the cities relies on resources provided by infrastructural networks. The robustness and resiliene of such structures are crucial in order to assess the quality of life of citizens in our countries.