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