Rumor spreading model considering rumor’s attraction in heterogeneous social networks

Xia, LL; Song, B; Zhang, L

Rumor spreading model considering rumor’s attraction in heterogeneous social networks

Xia, LL Song, B Zhang, L

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, 11067 LNCS pp. 734 - 745
Issue Date:: 2018-01-01

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Field	Value	Language
dc.contributor.author	Xia, LL	en_US
dc.contributor.author	Song, B	en_US
dc.contributor.author	Zhang, L	en_US
dc.date.issued	2018-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, 11067 LNCS pp. 734 - 745	en_US
dc.identifier.isbn	9783030000172	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/131717
dc.description.abstract	© Springer Nature Switzerland AG 2018. In this paper, we propose a modified susceptible-infected-removed (SIR) model with introduction of rumor’s attraction and establish corresponding mean-field equations to characterize the dynamics of SIR model on heterogeneous social networks. Then a steady-state analysis is conducted to investigate how the rumor’s attraction influences the threshold behavior and the final rumor size. Theoretical analysis and simulation results demonstrate that the rumor spreading threshold is related to the topological characteristics of underlying network and the infectivity of individual but is independent of the attraction of the rumor itself. In addition, whether a rumor spreads or not is determined by the relationship between the effective spreading rate and the spreading threshold. We also find that when a rumor’s attraction is very high, the effective spreading rate can easily reach the critical rumor spreading threshold, which leads to rumor spreading far and wide.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-030-00018-9_65	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Rumor spreading model considering rumor’s attraction in heterogeneous social networks	en_US
dc.type	Conference Proceeding
utslib.citation.volume	11067 LNCS	en_US
utslib.for	0805 Distributed Computing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	11067 LNCS	en_US

Abstract:

© Springer Nature Switzerland AG 2018. In this paper, we propose a modified susceptible-infected-removed (SIR) model with introduction of rumor’s attraction and establish corresponding mean-field equations to characterize the dynamics of SIR model on heterogeneous social networks. Then a steady-state analysis is conducted to investigate how the rumor’s attraction influences the threshold behavior and the final rumor size. Theoretical analysis and simulation results demonstrate that the rumor spreading threshold is related to the topological characteristics of underlying network and the infectivity of individual but is independent of the attraction of the rumor itself. In addition, whether a rumor spreads or not is determined by the relationship between the effective spreading rate and the spreading threshold. We also find that when a rumor’s attraction is very high, the effective spreading rate can easily reach the critical rumor spreading threshold, which leads to rumor spreading far and wide.

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http://hdl.handle.net/10453/131717