A Database Perspective of Social Network Analysis Data Processing Abstract
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ADatabasePerspectiveofSocialNetwork
AnalysisDataProcessing
MauroSanMart´ın∗,ClaudioGutierrez
DepartamentodeCienciasdelaComputaci´on-UniversidaddeChileAvenidaBlancoEncalada2120-Santiago-Chile.
Abstract
Interestinsocialnetworksisbecomingpervasiveanddatavolumesincreasedra-matically;however,currenttoolsandmodelsfordatastorageandmanipulationintheareastilllackestablishedmethodologiesofthefieldofdatabases.Forinstance,therearenostandardstorageformatspromotingreuse,sharingorcombinationofdatasetsfromdifferentsources,andavailableformatsrequireadjustmentofcol-lecteddatatotheirrepresentationalcapabilities,oftenexcludingpotentiallyusefuldata.
Inthisworkweshowthenecessityandpossibilityofenhancingdatamanagementforsocialnetworks.Themaintechnicalchallengecomesfromtheverynatureofnetworkeddataandofthequeriesandanalysisinvolved.Wepresentpreliminaryresultstowardsadatastorageandmanipulationmodelforsocialnetworkswhichnativelysupportsattributedanddynamicmultinets,usingthefullpotentialitiesofstandarddatabasetechniques.
FollowingFreeman’sideasonmethodologicalaspectsofsocialnetworkanalysisandbasedoncurrentpractices,wedeterminerequirements,describeasuitabledataworkflow,anddetectcurrentlimitationsandneeds.Asacase-studyweuseDBLP,anonlinenetworkofcomputerscienceauthorsandpublications.
Keywords:DataManagement,CollectingNetworkData,AcademicNetworks,CompleteNetworks,DataRepresentation
M.SanMart´ınwassupportedbyaMECESUPscholarshipandprojectFONDE-CYTN.1030810.C.GutierrezwassupportedbyprojectFONDECYTN.1030810andProyectoMilenioP04-067-F,CenterforWebResearch.∗msanmart@dcc.uchile.cl
ArticlepresentedatSunbeltXXVI20061Introduction
Theprominenceofsocialnetworksandtheirdatavolumesareincreasingdra-
matically;however,currenttoolsandmodelsfordatastorageandmanip-
ulationintheareastilllackestablishedmethodologiesofthefieldofdata
management.Todatemostofthecomputerassistedsocialnetworkanalysisis
beingdonewithtoolsorientedsolelytoanalysisitself,withlittlecareabout
theinherentdatamanagementissues,like:dataaccessinaproperlevelof
abstraction,automaticcollection,archivingandreuse,provisionofacommon
groundtosupportnetworkanalysisoverdataincrementallycollectedfrompos-
siblydifferentsources.Furthermore,theneedfordatamanagementsupport
isanexplicitandurgentissueduetotheneedofautomaticandcontinuous
datacollectionforextensiveanalysis(Tsvetovatetal.,2005).Thissituation
presentsanumberofopenproblemsrelatedtodatamanagementsupportof
socialnetworkdata,asituationthatisoccurringalsoinotherfieldsthatuse
networkdatatoo,likebiosciences(JagadishandOlken,2003a;Grayetal.,
2005).
AspointedoutbyFreeman(2004,ch.1),theextensiveworkdonebysocialnet-
workanalysiscommunity,sincethe1930’s(seealso:Scott,2000;Wasserman
andFaust,1994),hasconsolidatedacharacteristicdatamanagementworkflow
whichisdrivenbyastructuralintuition,asystematicdatacollectionandthe
useofvisualizationandmathematicalmodels(Freeman,2004).
Inthepastdecades,data/databasemodelshasbeendevisedbythedatabase
researchcommunityastheconceptualframeworksthatprovidethefounda-
tionstosolvedatamanagementproblemsforagivendomain.Socialnetworks
–independentoftheirorigin–havecommoncharacteristics(Newman,2003;
Barab´asiandBonabeau,2003;Freemanetal.,1992)usefultoprovideafoun-
dationforacommondatamodel,asdefinedbyCodd(1980),i.e.asaset
ofdatastructures,acollectionoftransformationandqueryoperators,and
integrityconstraints.
Thesocialnetworkanalysisdataworkflowcancertainlybenefitfromdata
managementtechniquesbasedonanappropriatedatamodel.
Todaythereexistsmanifolddatamodels,withdifferentdegreesofdevelop-
ment,buttheydonotprovidetheneededsupportforsocialnetworkanalysis.
Forexample,whilethedominantdb-relationaldatamodel1doesnotprovide
supporttobasicnetworkoperations(e.g.pathfindingandmotifsearching(Ja-
gadishandOlken,2003a)),otherdatamodels,likegraphdatamodels(Angles
andGuti´errez,2005b)andsemistructureddatamodels(Abitebouletal.,1999;
1Indatabaseliteraturethismodeliscalledrelationaldatamodel;wecallitinthispaperdb-relationaltoavoidconfusionswithrelationaldata.
2Suciu,1998;Buneman,1997),mayofferabettersupport,butarenotfullyde-
veloped.Acomprehensivereviewofrecentyearsactivityindatabaseanddata
miningconferences,showsthatdatabasesupportforsocialnetworks,backed
byacompletedatamodel,remainsanopenproblem.
Inthiswork,weshowhowaspeciallytailoreddatamodel,onthelinesof
graphandsemistructureddatamodels,willbenefitsocialnetworkanalysis.
OurstartingpointistheFreemanetal.(1992)maximalstructureexperiment
andtherequirementscollectedfromwellknownreferenceworkslikethoseof
WassermanandFaust(1994),Scott(2000)andCarringtonetal.(2005),from
recentlypublishedworks(Butts,2001;Jinetal.,1998;NewmanandPark,
2003;Doddsetal.,1998),andfromthefeaturesofexistingcomputational