• Publications
  • Influence
Finding and evaluating community structure in networks.
  • M. Newman, M. Girvan
  • Physics, Medicine
  • Physical review. E, Statistical, nonlinear, and…
  • 11 August 2003
We propose and study a set of algorithms for discovering community structure in networks-natural divisions of network nodes into densely connected subgroups. Our algorithms all share two definitiveExpand
  • 10,349
  • 1081
  • PDF
Modularity and community structure in networks.
  • M. Newman
  • Medicine, Computer Science
  • Proceedings of the National Academy of Sciences…
  • 17 February 2006
TLDR
In this article we have examined the problem of detecting community structure in networks, which is framed as an opti- mization task in which one searches for the maximal value of the quantity known as modularity over possible divisions of a network. Expand
  • 7,427
  • 605
  • PDF
Fast algorithm for detecting community structure in networks.
  • M. Newman
  • Physics, Medicine
  • Physical review. E, Statistical, nonlinear, and…
  • 22 September 2003
Many networks display community structure--groups of vertices within which connections are dense but between which they are sparser--and sensitive computer algorithms have in recent years beenExpand
  • 4,124
  • 407
  • PDF
Finding community structure in networks using the eigenvectors of matrices.
  • M. Newman
  • Mathematics, Medicine
  • Physical review. E, Statistical, nonlinear, and…
  • 10 May 2006
We consider the problem of detecting communities or modules in networks, groups of vertices with a higher-than-average density of edges connecting them. Previous work indicates that a robust approachExpand
  • 3,507
  • 296
  • PDF
Assortative mixing in networks.
  • M. Newman
  • Medicine, Physics
  • Physical review letters
  • 20 May 2002
A network is said to show assortative mixing if the nodes in the network that have many connections tend to be connected to other nodes with many connections. Here we measure mixing patterns in aExpand
  • 3,757
  • 295
  • PDF
Mixing patterns in networks.
  • M. Newman
  • Physics, Medicine
  • Physical review. E, Statistical, nonlinear, and…
  • 19 September 2002
We study assortative mixing in networks, the tendency for vertices in networks to be connected to other vertices that are like (or unlike) them in some way. We consider mixing according to discreteExpand
  • 2,168
  • 167
  • PDF
Analysis of weighted networks.
  • M. Newman
  • Mathematics, Physics
  • Physical review. E, Statistical, nonlinear, and…
  • 20 July 2004
The connections in many networks are not merely binary entities, either present or not, but have associated weights that record their strengths relative to one another. Recent studies of networksExpand
  • 1,888
  • 148
  • PDF
Spread of epidemic disease on networks.
  • M. Newman
  • Physics, Biology
  • Physical review. E, Statistical, nonlinear, and…
  • 30 April 2002
The study of social networks, and in particular the spread of disease on networks, has attracted considerable recent attention in the physics community. In this paper, we show that a large class ofExpand
  • 2,419
  • 123
  • PDF
Coauthorship networks and patterns of scientific collaboration
  • M. Newman
  • Medicine, Mathematics
  • Proceedings of the National Academy of Sciences…
  • 6 April 2004
By using data from three bibliographic databases in biology, physics, and mathematics, respectively, networks are constructed in which the nodes are scientists, and two scientists are connected ifExpand
  • 1,471
  • 95
  • PDF
Why social networks are different from other types of networks.
  • M. Newman, J. Park
  • Physics, Mathematics
  • Physical review. E, Statistical, nonlinear, and…
  • 26 May 2003
We argue that social networks differ from most other types of networks, including technological and biological networks, in two important ways. First, they have nontrivial clustering or networkExpand
  • 1,180
  • 49
  • PDF