Title: Studying the effect of community structure for seed selection in an influence model
Authors: Carolina Ribeiro Xavier; Vinícius Da Fonseca Vieira; Alexandre Gonçalves Evsukoff
Addresses: Graduate Program in Computer Science, Federal University of São João Del Rei (UFSJ), São João Del Rei, MG, Brazil ' Graduate Program in Computer Science, Federal University of São João Del Rei (UFSJ), São João Del Rei, MG, Brazil ' COPPE, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, RJ, Brazil
Abstract: This paper presents a study of influence spreading in real complex networks which shows that community structure in networks can be used to guide the selection of seed nodes to spread information and ideas over the network. The results obtained by the application of the methodology to a set of benchmark networks suggest that the distribution of seeds among the central nodes of the network's communities can increase the range of information spreading when compared to other common methods using central nodes as seeds considering only the global context of the network.
Keywords: influence; communities; modularity; spreading activation model; SPA.
International Journal of Information and Decision Sciences, 2019 Vol.11 No.4, pp.300 - 319
Received: 05 Oct 2017
Accepted: 26 May 2018
Published online: 05 Nov 2019 *