The London Institute’s papers are the official record of our discoveries. They allow others to build on and apply our work. Each one is the result of many months of research, so we strive to make them clear, inspiring and beautiful, and publish them in leading journals.

Image for the paper "Tackling information asymmetry in networks: a new entropy-based ranking index"
Complex networks

Information asymmetry

Network users who have access to the network’s most informative node, as quantified by a novel index, the InfoRank, have a competitive edge.

PBPaolo BaruccaGCGuido CaldarelliTS
Journal of Statistical Physics
Image for the paper "From ecology to finance (and back?): a review on entropy-based null models for the analysis of bipartite networks"
Financial networks

From ecology to finance

Bipartite networks model the structures of ecological and economic real-world systems, enabling hypothesis testing and crisis forecasting.

GCGuido CaldarelliMSTSFS
Journal of Statistical Physics
Image for the paper "Bootstrapping topology and systemic risk of complex networks using the fitness model"
Financial risk

Bootstrapping topology and risk

Information about 10% of the links in a complex network is sufficient to reconstruct its main features and resilience with the fitness model.

GCGuido CaldarelliNMSBMPAG
Journal of Statistical Physics