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Vectorised Spreading Activation algorithm for centrality measurement

Troussov, A and Dařena, F and Žižka, J and Parra, D and Brusilovsky, P (2011) Vectorised Spreading Activation algorithm for centrality measurement. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 59 (7). 469 - 476. ISSN 1211-8516

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Abstract

Spreading Activation is a family of graph-based algorithms widely used in areas such as information retrieval, epidemic models, and recommender systems. In this paper we introduce a novel Spreading Activation (SA) method that we call Vectorised Spreading Activation (VSA). VSA algorithms, like "traditional" SA algorithms, iteratively propagate the activation from the initially activated set of nodes to the other nodes in a network through outward links. The level of the node's activation could be used as a centrality measurement in accordance with dynamic model-based view of centrality that focuses on the outcomes for nodes in a network where something is flowing from node to node across the edges. Representing the activation by vectors allows the use of the information about various dimensionalities of the flow and the dynamic of the flow. In this capacity, VSA algorithms can model multitude of complex multidimensional network flows. We present the results of numerical simulations on small synthetic social networks and multi dimensional network models of folksonomies which show that the results of VSA propagation are more sensitive to the positions of the initial seed and to the community structure of the network than the results produced by traditional SA algorithms. We tentatively conclude that the VSA methods could be instrumental to develop scalable and computationally efficient algorithms which could achieve synergy between computation of centrality indexes with detection of community structures in networks. Based on our preliminary results and on improvements made over previous studies, we foresee advances and applications in the current state of the art of this family of algorithms and their applications to centrality measurement.

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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Troussov, A
Dařena, F
Žižka, J
Parra, D
Brusilovsky, Ppeterb@pitt.eduPETERB0000-0002-1902-1464
Date: 1 January 2011
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
Volume: 59
Number: 7
Page Range: 469 - 476
DOI or Unique Handle: 10.11118/actaun201159070469
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISSN: 1211-8516
Date Deposited: 03 Aug 2012 20:27
Last Modified: 04 Feb 2019 15:58
URI: http://d-scholarship.pitt.edu/id/eprint/13309

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