A Pólya urn approach to information filtering in complex networks

Marcaccioli, Riccardo and Livan, Giacomo (2019) A Pólya urn approach to information filtering in complex networks. Nature Communications, 10 (1). ISSN 2041-1723

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Abstract

The increasing availability of data demands for techniques to filter information in large complex networks of interactions. A number of approaches have been proposed to extract network backbones by assessing the statistical significance of links against null hypotheses of random interaction. Yet, it is well known that the growth of most real-world networks is non-random, as past interactions between nodes typically increase the likelihood of further interaction. Here, we propose a filtering methodology inspired by the Pólya urn, a combinatorial model driven by a self-reinforcement mechanism, which relies on a family of null hypotheses that can be calibrated to assess which links are statistically significant with respect to a given network’s own heterogeneity. We provide a full characterization of the filter, and show that it selects links based on a non-trivial interplay between their local importance and the importance of the nodes they belong to.

Item Type:	Article
Additional Information:	© 2019 The Authors
Divisions:	Systemic Risk Centre
Subjects:	H Social Sciences > H Social Sciences (General)
Date Deposited:	28 Feb 2019 08:45
Last Modified:	25 Oct 2024 02:36
URI:	http://eprints.lse.ac.uk/id/eprint/100153

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