Analysis of Communities Evolution in Dynamic Social Networks

Autor:	Nikolai Nefedov
Rok vydání:	2013
Předmět:	Modularity maximization Dynamic network analysis Laplacian spectrum Computer science Outlier Snapshot (computer storage) Data mining Greedy algorithm computer.software_genre Random walk Cluster analysis computer
Zdroj:	Complex Networks IV ISBN: 9783642368431 CompleNet
DOI:	10.1007/978-3-642-36844-8_4
Popis:	In this paper we present a framework to study evolution of communities in dynamic networks. A dynamic network is represented by a sequence of static graphs named as network snapshots.We introduce a distance measure between static graphs to study similarity among network snapshots and to detect outlier events. To find a detailed structure within each network snapshot we used a modularity maximization algorithm based on a fast greedy search extended with a random walk approach. Community detection often results in a different number of communities in different network snapshots. To make communities evolution studies feasible we propose a greedy method to match clustering labels assigned to different networks. The suggested framework is applied for analysis of dynamic networks built from real-world mobile datasets.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::fb187c833a435c75d30cc43d41ca5ac7 https://doi.org/10.1007/978-3-642-36844-8_4 Zobrazit plný text záznamu