Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/18981
DC FieldValueLanguage
dc.contributor.authorTsapatsoulis, Nicolas-
dc.contributor.authorAnastasopoulou, Vasiliki-
dc.contributor.authorNtalianis, Klimis S.-
dc.date.accessioned2020-09-16T07:07:40Z-
dc.date.available2020-09-16T07:07:40Z-
dc.date.issued2019-11-04-
dc.identifier.citationIEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing, Cyber Science and Technology Congress, 2019, 5-8 August, Fukuoka, Japanen_US
dc.identifier.isbn978-1-7281-3024-8-
dc.identifier.urihttps://ktisis.cut.ac.cy/handle/10488/18981-
dc.description.abstractThe central community of social networks, usually represented through the highest degree k-core of the corresponding graph, is proposed here as a compact representation of large social networks. We show that the central community of egocentric social media networks, such as the ego networks on Twitter and Instagram, tell us much more about the actual influence of the ego than the whole egocentric network itself. We also propose a novel genetic algorithm for the identification of central community of egocentric social networks and we examine the importance of the proper initialisation of this algorithm. The actual Twitter ego networks we used in our experiments along with the corresponding Python code are made publicly available for anyone who wishes to use them.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relationEnhaNcing seCurity And privacy in the Social wEb: a user centered approach for the protection of minorsen_US
dc.rights© IEEEen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectCommunity detectionen_US
dc.subjectDegeneracyen_US
dc.subjectGenetic algorithmsen_US
dc.subjectGraph partitioningen_US
dc.subjectK-coreen_US
dc.subjectSocial networksen_US
dc.subjectTwitter ego networksen_US
dc.titleThe Central Community of Twitter ego-Networks as a Means for Fake Influencer Detectionen_US
dc.typeConference Papersen_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationNational and Kapodistrian University of Athensen_US
dc.collaborationUniversity of West Atticaen_US
dc.subject.categoryComputer and Information Sciencesen_US
dc.countryCyprusen_US
dc.countryGreeceen_US
dc.subject.fieldNatural Sciencesen_US
dc.publicationPeer Revieweden_US
dc.relation.conferenceIEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing, Cyber Science and Technology Congressen_US
dc.identifier.doi10.1109/DASC/PiCom/CBDCom/CyberSciTech.2019.00042en_US
cut.common.academicyear2019-2020en_US
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.openairetypeconferenceObject-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.grantfulltextnone-
crisitem.project.funderEC-
crisitem.project.grantnoENCASE-
crisitem.project.fundingProgramH2020-
crisitem.project.openAireinfo:eu-repo/grantAgreement/EC/H2020/691025-
crisitem.author.deptDepartment of Communication and Internet Studies-
crisitem.author.facultyFaculty of Communication and Media Studies-
crisitem.author.orcid0000-0002-6739-8602-
crisitem.author.parentorgFaculty of Communication and Media Studies-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers - poster -presentation
CORE Recommender
Show simple item record

Page view(s)

15
checked on Oct 25, 2020

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons