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1、ASurveyofPredictionUsingSocialMediaShengYuandSubhashKakDepartmentofComputerScience,OklahomaStateUniversityStillwater,Oklahoma,U.S.A.74078{yshe,subhashk}@cs.okstate.eduAbstract:Socialmediacomprisesinteractiveapplicationsandplatformsforcreating,sharingandexchangeofuser-ge
2、neratedcontents.Thepasttenyearshavebroughthugegrowthinsocialmedia,especiallyonlinesocialnetworkingservices,anditischangingourwaystoorganizeandcommunicate.Itaggregatesopinionsandfeelingsofdiversegroupsofpeopleatlowcost.Miningtheattributesandcontentsofsocialmediagivesusan
3、opportunitytodiscoversocialstructurecharacteristics,analyzeactionpatternsqualitativelyandquantitatively,andsometimestheabilitytopredictfuturehumanrelatedevents.Inthispaper,wefirstlydiscusstherealmswhichcanbepredictedwithcurrentsocialmedia,thenoverviewavailablepredictors
4、andtechniquesofprediction,andfinallydiscusschallengesandpossiblefuturedirections.Keywords:socialmedia,socialnetwork,socialnetworkingservice,user-generatedcontents,prediction1.IntroductionSocialmediaareplatformsthatallowcommonpersonstocreateandpublishcontents.Twoworldwid
5、epopularsocialmediawebsites,TwitterandFacebook,demonstrateitsexplosivegrowthandprofoundinfluence.BothTwitterandFacebookareinthetop10most-visitedwebsitesintheworldaccordingtoAlexaranking[1].Facebookhasmorethan800millionactiveusers[2],andbyMarch2011,onTwitter,therewereabo
6、ut140millioninformationpiecescreatedandtransferreddaily[3].Thereisotherspecializedsocialmediathatarefocusedonentertainment,sports,financeandpolitics.Sincetherearemanyuserssharingtheiropinionsandexperiencesviasocialmedia,thereisaggregationofpersonalwisdomanddifferentview
7、points.Suchaggregationhaslimitationsasviewpointsaresubjecttochangewithtime.Inasensethesocialmediapredictionproblemisparalleledbypredictionoffinancialtimeseriesbasedonpasthistory,whichhasitsusesintrading.Ingeneral,ifextractedandanalyzedproperly,thedataonsocialmediacanlea
8、dtousefulpredictionsofcertainhumanrelatedevents.Suchpredictionhasgreatbenefitsinmanyrealms,suchasfinance,produ