Efficiency of Algorithms for Computing Influence and Information Spreading on Social Networks

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dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorKuikka, Vesaen_US
dc.contributor.authorAalto, Henriken_US
dc.contributor.authorIjäs, Matiasen_US
dc.contributor.authorKaski, Kimmo K.en_US
dc.contributor.departmentDepartment of Computer Scienceen
dc.contributor.groupauthorKaski Kimmo groupen
dc.contributor.organizationFinnish Defence Research Agencyen_US
dc.contributor.organizationEficodeen_US
dc.date.accessioned2022-09-21T06:06:57Z
dc.date.available2022-09-21T06:06:57Z
dc.date.issued2022-08en_US
dc.descriptionFunding Information: We acknowledge that the original idea and software implementation of Algorithm 3 has been a result of the cooperation between Matias Ijäs and Janne Levijoki [15]. The work of Ijäs and Levijoki is an efficient implementation of the influence spreading model that was first published in [28]. Publisher Copyright: © 2022 by the authors.
dc.description.abstractModelling interactions on complex networks needs efficient algorithms for describing processes on a detailed level in the network structure. This kind of modelling enables more realistic applications of spreading processes, network metrics, and analyses of communities. However, different real-world processes may impose requirements for implementations and their efficiency. We discuss different transmission and spreading processes and their interrelations. Two pseudo-algorithms are presented, one for the complex contagion spreading mechanism using non-self-avoiding paths in the modelling, and one for simple contagion processes using self-avoiding paths in the modelling. The first algorithm is an efficient implementation that can be used for describing social interaction in a social network structure. The second algorithm is a less efficient implementation for describing specific forms of information transmission and epidemic spreading.en
dc.description.versionPeer revieweden
dc.format.extent15
dc.format.extent1-15
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationKuikka, V, Aalto, H, Ijäs, M & Kaski, K K 2022, ' Efficiency of Algorithms for Computing Influence and Information Spreading on Social Networks ', Algorithms, vol. 15, no. 8, 262, pp. 1-15 . https://doi.org/10.3390/a15080262en
dc.identifier.doi10.3390/a15080262en_US
dc.identifier.issn1999-4893
dc.identifier.otherPURE UUID: c1182312-18b4-4b7b-9aa4-6f070dade1d3en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/c1182312-18b4-4b7b-9aa4-6f070dade1d3en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85137267482&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/88351781/Efficiency_of_Algorithms_for_Computing_Influence_and_Information_Spreading_on_Social_Networks.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/116883
dc.identifier.urnURN:NBN:fi:aalto-202209215681
dc.language.isoenen
dc.publisherMDPI AG
dc.relation.ispartofseriesALGORITHMSen
dc.relation.ispartofseriesVolume 15, issue 8en
dc.rightsopenAccessen
dc.subject.keywordcentrality measuresen_US
dc.subject.keywordcommunity detectionen_US
dc.subject.keywordepidemic spreadingen_US
dc.subject.keywordinfluence spreadingen_US
dc.subject.keywordinformation spreadingen_US
dc.subject.keywordmodelling social networksen_US
dc.subject.keywordpseudo-algorithmen_US
dc.subject.keywordscalable algorithmen_US
dc.subject.keywordsocial media networksen_US
dc.subject.keywordsocial networksen_US
dc.titleEfficiency of Algorithms for Computing Influence and Information Spreading on Social Networksen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion

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