We propose a framework to unfold the ego-centered community structure of a given node in a network. The framework is not based on the optimization of a quality function, but on the study of the irregularity of the decrease of a similarity measure. It is a practical use of the notion of multi-ego-centered community and we validate the pertinence of the approach on a real-world network of wikipedia pages.

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**Community detection in attributed graphs.**Christine Largeron*2017, April 25, Room 24-25/405*- affinity index algorithm analysis antipaedo attack bipartite blog network blogs capitalisme social Cascade centrality clustering communities community detection community structure complex network complex networks complex systems compression connected graphs data mining debian degree distribution degree peeling diameter diffusion diffusion phenomena distributed measurements DynamicNetworks dynamics edge-Markovian evolving graph eDonkey ego-centered ego-centered communities email epidemiology event detection evolving graphs evolving networks exploration failure fixed points formal concepts gossip graph graph algorithm graph decompositions Graphs hierarchical clustering honeypot influence influence ranking interaction networks internal links internet Internet topology intrinsic time IP-level ip exchanges lattice leaders link prediction long term communities markovian model measurement mesure d’influence metrics Metrology mobile networks Modelling modularity multi-ego-centered communities multi-scale multipartite graph network dynamics node proximity node similarity opinion dynamics outliers p2p P2P dynamics P2P networks parametric paris paris-traceroute path-vector routing pedophile activity phone power-law radar random graph random walks reachability robustness routing routing tables scale-free security simulation simulations sir social networks spreading spreading cascades stability statistical analysis stochastic process three-state cellular automata time-varying Topology traceroute triangles twitter UDP user profiles viral marketing visualization web wifi