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基于先验估计的传播中心溯源算法.docx

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基于先验估计的传播中心溯源算法 Title:PropagationCenterTracingAlgorithmbasedonPriorEstimation Abstract: Inrecentyears,therapidtransmissionofinformationandtheproliferationofonlinesocialnetworkshavemadeitincreasinglyimportanttotracetheoriginofinformationandtrackdownthesourcesofspreadingevents.Inthispaper,weproposeapropagationcentertracingalgorithmbasedonpriorestimation.Thisalgorithmaimstoaccuratelyidentifytheinitialsourceofinformationinacascadeandeffectivelytrackthepathwaysofinformationspreading.Thealgorithmcombinespriorestimationmethodswithnetworkanalysistechniques,providingasystematicapproachforsourcetracinginlarge-scalecascades. 1.Introduction: Withthewidespreaduseofsocialmediaplatforms,informationspreadsrapidly,causingsignificantimpactandinfluenceonpublicopinion.Itiscrucialtounderstandhowinformationpropagatesinordertomitigatethedisseminationoffalseinformationorharmfulcontent.Traditionaltracingmethods,suchasbacktrackingandtime-stampanalysis,oftensufferfromlimitationsintermsofaccuracy,scalability,andresourceusage.Therefore,anefficientandreliablealgorithmisneededforsourcetracinginlarge-scalecascades. 2.PriorEstimation: Priorestimationreferstotheestimationofthelikelysourcesofinformationpropagationbasedonavailableevidenceandknowledge.Itinvolvesanalyzingvariousfactors,suchasuserinfluence,networktopology,andcontentcharacteristics.Byincorporatingpriorestimationmethodsintothetracingalgorithm,wecannarrowdownthesearchspaceandfocusonpotentialsources,therebyimprovingefficiencyandaccuracy. 3.TracingAlgorithm: Theproposedalgorithmconsistsofseveralkeysteps.Firstly,itconstructsthecascadenetworkbymodelingtheinformationpropagationprocessasadirectedgraph.Eachnodeinthegraphrepresentsauser,andtheedgesrepresenttheflowofinformationfromoneusertoanother.Then,itappliespriorestimationtechniquestoranktheusersbasedontheirlikelihoodofbeingthesourceofthecascade.Thisrankingcanbeachievedthroughvariousmethods,includingcentralityanalysis,machinelearningmodels,oracombinationofboth.Thealgorithmtheniterativelyprunesth