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1、哈尔滨工业大学硕士学位论文AbstractWiththeappearanceofmicroblog,anewnetworkeraiscoming.Manystudents,teachers,academicsanduniversitiesbecomeimportantpartofSinaWeibousersthatcannotbeignored.Thosegrouphasincreasinglyimpacttothesociety.Inrecentyears,withthepubliceventsaboutcampu
2、sonsocialnetworkhappenedmanytimes,itshowsthattheinfluenceofcampusinsocialnetworkisbecomingbigger.Therefore,studyingonimpactevaluationmethodofcampususersnotonlycantakeprecautionsagainstpublicopinion,butalsocanmaintaincampusimageandhelptosupervisethecampusmicrobl
3、og.Basedonthis,thisarticletrytosolvethisproblemfromtwoaspectsasfollows:Firstly,westudyonthemodeltodetectspamaccountonSinaWeibo.TheexplosivelyincreasingspammersonSinaWeibowillcausedataexpansionandunreal,andaffecttheresultofimpactevaluationeventually.Thenadecisio
4、ntreeclassificationmodelisestablishedtodetectspammersonSinaWeibo.WeuseWEKA,amachinelearningtool,operatedataprocessingandmodelbuilding.Totestthevalidityofthemodel,weusetencrossvalidationsandtwotestsetstotesttheclassificationaccuracyrespectively,theclassification
5、accuraciesareallover90%.Theresultsprovethemodeliscapableofidentifyingthespamaccounts.Moreover,wedetectspammersonthefollowingsoftenrepresentativecampusmicroblogs.Theresultshowsthattherearebetween11%-25%spamaccountsinthosecampusmicroblogs.Secondly,westudyimpactev
6、aluationmethodofuniversitymicroblogsonSinaWeibo.Inthispaper,wechoosetwoaspects,microblogaudienceanddisseminationcapabilities,toevaluatetheimpactofuniversitymicroblogs.Wealsoempiricallyanalyzethebasicfeaturesoftencampusmicrobloggingusers,includingFollowings,Foll
7、owingsofFollowings,repostsandcomments.Wefindthatthesefeaturesdatahavestrongfluctuations,andissensitivetothepeakvalue.Inordertosolvethedefectsofthosebasicfeatures,wetrytoapplyh-indexmethodtomeasureimpactevaluationofmicroblog.Accordingtotheempiricalanalysisoftenu
8、niversities,h-indexcanbeeffctivelyusedinthefieldofmicroblogimpactevaluation.Finally,weanalyzethecontentofthehighestrepostcampusmicrobloggingsandfindseveninformationdissemina
