Community structure in social and biological networks英文资料.pdf

Community structure in social and biological networks Michelle Girvan1,2 and M. E. J. Newman1 1Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501 2Department of Physics, Cornell University, Clark Hall, Ithaca, NY 14853–2501 1 (Dated: December 7, 2001) 0 0 A number of recent studies have focused on the statistical properties of networked systems such 2 as social networks and the World-Wide Web. Researchers have concentrated particularly on a few properties which seem to be common to many networks: the small-world property, power-law c degree distributions, and network transitivity. In this paper, we highlight another property which is e found in many networks, the property of community structure, in which network nodes are joined D together in tightly-knit groups between which there are only looser connections. We propose a new 7 method for detecting such communities, built around the idea of using centrality indices to find community boundaries. We test our method on computer generated and real-world graphs whose ] community structure is already known, and find that it detects this known structure with high h sensitivity and reliability. We also apply the method to two networks whose community structure is c not well-known—a collaboration network and a food web—and find that it detects significant and e informative community divisions in both cases. m - t a