Peer Influence Groups: Identifying Dense Clusters in Large Networks

Citation

Moody, J. (2001). Peer Influence Groups: Identifying Dense Clusters in Large Networks. Social Networks. vol. 23 pp. 261-283

Abstract

Sociologists have seen a dramatic increase in the size and availability of social network data. This represents a poverty of riches, however, since many of our analysis techniques cannot handle the resulting large (tens to hundreds of thousands of nodes) networks. In this paper, I provide a method for identifying dense regions within large networks based on a peer influence model. Using software familiar to most sociologists, the method reduces the network to a set of m position variables that can then be used in fast cluster analysis programs. The method is tested against simulated networks with a known small-world structure showing that the underlying clusters can be accurately recovered. I then compare the performance of the procedure with other subgroup detection algorithms on the MacRea and Gagnon prison friendship data and a larger adolescent friendship network, showing that the algorithm replicates other procedures for small networks and outperforms them on the larger friendship network.

URL

https://doi.org/10.1016/S0378-8733(01)00042-9

Keyword(s)

Friendship

Reference Type

Journal Article

Journal Title

Social Networks

Author(s)

Moody, J.

Year Published

2001

Volume Number

Pages

261-283

DOI

10.1016/S0378-8733(01)00042-9