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Scaling and Percolation in the Small-World Network Model

Newman, M. E. J.; Watts, D. J. - Santa Fe Institute - 1999

In this paper we study the small-world network model of Watts and Strogatz, which mimics some aspects of the structure of networks of social interactions. We argue that there is one non-trivial length-scale in the model, analogous to the correlation length in other systems, which is well-defined...

Persistent link: https://www.econbiz.de/10005837720

Ego-Centered Networks and the Ripple Effect

Newman, M. E. J. - Santa Fe Institute - 2001

Recent work has demonstrated that many social networks, and indeed many networks of other types also, have broad distributions of vertex degree. Here we show that this has a substantial impact on the shape of ego-centered networks, i.e., sets of network vertices that are within a given distance...

Persistent link: https://www.econbiz.de/10005790683

The Topology of Technology Graphs: Small World Patterns in Electronic Circuits

Cancho, Ramon Ferrer i; Janssen, Christiaan; Solé, … - Santa Fe Institute - 2001

Recent theoretical studies and extensive data analyses have revealed a common feature displayed by biological, social and technological networks: the presence of small world patterns. Here we analyse this problem by using several graphs obtained from one of the most common technological systems:...

Persistent link: https://www.econbiz.de/10005790730

Community Structure in Social and Biological Networks

Girvan, Michelle; Newman, M. E. J. - Santa Fe Institute - 2001

A number of recent studies have focused on the statistical properties of networked systems such 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 degree...

Persistent link: https://www.econbiz.de/10005790804

Fast Approximation Algorithms for Finding Node-Independent Paths in Networks

White, Douglas R.; Newman, M. E. J. - Santa Fe Institute - 2001

-hard problem, taking exponentially long to run to completion. In this paper, we present an approximation algorithm which gives good …-case time which is linear in the graph size. A variant of the same algorithm can also calculate all the k-components of a graph … in the same approximation. Our algorithm is found empirically to work with better than 99% accuracy on random graphs and …

Persistent link: https://www.econbiz.de/10005790851