title: Observability transition in real networks.
abstract: We consider the observability model in networks with arbitrary topologies. We introduce a system of coupled nonlinear equations, valid under the locally treelike ansatz, to describe the size of the largest observable cluster as a function of the fraction of directly observable nodes present in the network. We perform a systematic analysis on 95 real-world graphs and compare our theoretical predictions with numerical simulations of the observability model. Our method provides almost perfect predictions in the majority of the cases, even for networks with very large values of the clustering coefficient. Potential applications of our theory include the development of efficient and scalable algorithms for real-time surveillance of social networks, and monitoring of technological networks.
authors.affiliation: Department of Physics and Astronomy, Northwestern University, Evanston, Illinois 60208, USA.
authors.forename: Yang
authors.initials: Y
authors.lastname: Yang
authors.affiliation: Center for Complex Networks and Systems Research, School of Informatics and Computing, Indiana University, Bloomington, Indiana 47408, USA.
authors.forename: Filippo
authors.initials: F
authors.lastname: Radicchi