208 citations · 443 across the 4 of their papers we have counts for
8 papers
Exploring limits to prediction in complex social systems
Travis Martin, Jake M. Hofman, Amit Sharma +2
How predictable is success in complex social systems? In spite of a recent profusion of prediction studies that exploit online social and information network data, this question re…
Structural inference for uncertain networks
Travis Martin, Brian Ball, M. E. J. Newman
In the study of networked systems such as biological, technological, and social networks the available data are often uncertain. Rather than knowing the structure of a network exac…
Identification of core-periphery structure in networks
Xiao Zhang, Travis Martin, M. E. J. Newman
Many networks can be usefully decomposed into a dense core plus an outlying, loosely-connected periphery. Here we propose an algorithm for performing such a decomposition on empiri…
Equitable random graphs
M. E. J. Newman, Travis Martin
Random graph models have played a dominant role in the theoretical study of networked systems. The Poisson random graph of Erdos and Renyi, in particular, as well as the so-called…
Localization and centrality in networks
Travis Martin, Xiao Zhang, M. E. J. Newman
Eigenvector centrality is a common measure of the importance of nodes in a network. Here we show that under common conditions the eigenvector centrality displays a localization tra…
The small-world effect is a modern phenomenon
Seth A. Marvel, Travis Martin, Charles R. Doering +2
The "small-world effect" is the observation that one can find a short chain of acquaintances, often of no more than a handful of individuals, connecting almost any two people on th…