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1、AnIntroductiontoCommunityDetectioninMulti-layeredSocialNetwork11,21,2PiotrBródka,TomaszFilipowski,PrzemysławKazienko1WrocławUniversityofTechnology,Wyb.Wyspiańskiego27,50-370Wrocław,Poland2ResearchEngineeringCenterSp.zo.o.,ul.Strzegomska46B,53-611Wrocł
2、aw,Polandpiotr.brodka@pwr.wroc.pl,tomasz.filipowski@pwr.wroc.pl,kazienko@pwr.wroc.plAbstract:Socialcommunitiesextractionandtheirdynamicsareoneofthemostimportantproblemsintoday’ssocialnetworkanalysis.Duringlastfewyears,manyresearchershaveproposedtheiro
3、wnmethodsforgroupdiscoveryinsocialnetworks.However,almostnoneofthemhavenoticedthatmodernsocialnetworksaremuchmorecomplexthanfewyearsago.DuetovastamountofdifferentdataaboutvarioususeractivitiesavailableinITsystems,itispossibletodistinguishthenewclassof
4、socialnetworkscalledmulti-layeredsocialnetwork.Forthatreason,thenewapproachtocommunitydetectioninthemulti-layeredsocialnetwork,whichutilizesmulti-layerededgeclusteringcoefficientisproposedinthepaper.Keywords:socialnetwork,multi-layeredsocialnetwork,co
5、mmunitiesinsocialnetworks,communityextraction,socialnetworkanalysis,multi-layerededgeclusteringcoefficient1IntroductionAreaofsciencewhichinrecentyearsisrapidlygrowingissocialnetworkanalysis.Oneofthemainreasonsforthisisgrowingnumberofdifferentsocialnet
6、workingsystemsandsimplewaytoobtaindatafromwhichwecanextractthosesocialnetworks.Dependingonthetypeofsocialnetworkwewanttobuild,datacanbefoundinvariousplaces,e.g.:blogs[1],telecommunicationdata[2],bibliographicdata[3],socialserviceslikeFacebook[9],e-mai
7、lsystems[10]andmore.Groupextractionisamongthosetopicswhicharousethegreatestinterestinthedomainofsocialnetworkanalysis.Findinggroupsamongthesystemusersopensthenewpossibilitiesandcanbeutilizeinsuchdisciplinesashumanresourcemanagement,advertisement,infor
8、mationpropagationandlotsofothers.Manymethodsandalgorithmshavebeenproposed[3],[8].Theyarebecomingfaster[2]andbetterreflecttherealgroupsinsocialnetwork[6].Theseupgradeshavetobesignificantsincesocialnetworksaregrowingveryfastthosedays.Howeverfewy
