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A Matrix Iteration for Dynamic Network Summaries.

Abstract:
We propose a new algorithm for summarizing properties of large-scale time-evolving networks. This type of data, recording connections that come and go over time, is generated in many modern applications, including telecommunications and online human social behavior. The algorithm computes a dynamic measure of how well pairs of nodes can communicate by taking account of routes through the network that respect the arrow of time. We take the conventional approach of downweighting for length (messages become corrupted as they are passed along) and add the novel feature of downweighting for age (messages go out of date). This allows us to generalize widely used Katz-style centrality measures that have proved popular in network science to the case of dynamic networks sampled at nonuniform points in time. We illustrate the new approach on synthetic and real data. © 2013 Society for Industrial and Applied Mathematics.

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Publisher copy:
10.1137/110855715

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author


Journal:
SIAM Review More from this journal
Volume:
55
Issue:
1
Pages:
118-128
Publication date:
2013-01-01
DOI:
EISSN:
1095-7200
ISSN:
0036-1445


Language:
English
Keywords:
Pubs id:
pubs:405484
UUID:
uuid:0129c079-b882-4c3f-b343-e000da7ff233
Local pid:
pubs:405484
Source identifiers:
405484
Deposit date:
2013-11-16
ARK identifier:

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