Reformulations of the Map Equation for Community Finding and Blockmodelling

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Title: Reformulations of the Map Equation for Community Finding and Blockmodelling
Authors: Hurley, Neil J.
Duriakova, Erika
Permanent link: http://hdl.handle.net/10197/8413
Date: 28-Aug-2015
Abstract: Among the many community-finding algorithms that have been proposed in the last decade and more, the Infomapalgorithm of Rosvall and Bergstrom has proven among the best. The algorithm finds good community structure in directed aswell as undirected networks by abstracting information flow inthe network as a random walk. In this paper, we reformulate the objective in terms of the Kullback-Leibler distance between thedistribution of the random walk transitions and that of a modelwalk. The choice of model can be used to constrain the typeof partition that the method extracts. This generalisation makesthe method suitable for extracting other types of meso-structurefrom the network, enabling the analyst to explicitly control thetype of extracted structure.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: IEEE
Copyright (published version): 2015 IEEE
Keywords: Machine learningStatisticsInfomap methodGeneralised blockmodelling
DOI: 10.1145/2808797.2809356
Language: en
Status of Item: Peer reviewed
Conference Details: The 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2015), Paris, France, 25-28 August 2015
ISBN: 9781450338547
Appears in Collections:Computer Science Research Collection
Insight Research Collection

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