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1、1Twittermoodpredictsthestockmarket.JohanBollen1;?,HuinaMao1;?,Xiao-JunZeng2.?:authorsmadeequalcontributions.Abstract—Behavioraleconomicstellsusthatemotionscansentimentfromblogs.Inaddition,Googlesearchquerieshaveprofoundlyaffectindividualbehavioranddecision-mak
2、ing.Doesbeenshowntoprovideearlyindicatorsofdiseaseinfectionthisalsoapplytosocietiesatlarge,i.e.cansocietiesexperienceratesandconsumerspending[14].[9]investigatestherelationsmoodstatesthataffecttheircollectivedecisionmaking?Bybetweenbreakingfinancialnewsandstock
3、pricechanges.extensionisthepublicmoodcorrelatedorevenpredictiveofeconomicindicators?HereweinvestigatewhethermeasurementsMostrecently[13]provideaground-breakingdemonstrationofcollectivemoodstatesderivedfromlarge-scaleTwitterfeedsofhowpublicsentimentrelatedtomov
4、ies,asexpressedonarecorrelatedtothevalueoftheDowJonesIndustrialAverageTwitter,canactuallypredictboxofficereceipts.(DJIA)overtime.WeanalyzethetextcontentofdailyTwitterAlthoughnewsmostcertainlyinfluencesstockmarketfeedsbytwomoodtrackingtools,namelyOpinionFindertha
5、tmeasurespositivevs.negativemoodandGoogle-ProfileofMoodprices,publicmoodstatesorsentimentmayplayanequallyStates(GPOMS)thatmeasuresmoodintermsof6dimensionsimportantrole.Weknowfrompsychologicalresearchthat(Calm,Alert,Sure,Vital,Kind,andHappy).Wecross-validateemot
6、ions,inadditiontoinformation,playansignificantroletheresultingmoodtimeseriesbycomparingtheirabilitytoinhumandecision-making[16],[18],[39].Behavioralfinancedetectthepublic’sresponsetothepresidentialelectionandhasprovidedfurtherproofthatfinancialdecisionsaresig-Tha
7、nksgivingdayin2008.AGrangercausalityanalysisandaSelf-OrganizingFuzzyNeuralNetworkarethenusedtonificantlydrivenbyemotionandmood[19].Itisthereforeinvestigatethehypothesisthatpublicmoodstates,asmeasuredbyreasonabletoassumethatthepublicmoodandsentimentcantheOpinion
8、FinderandGPOMSmoodtimeseries,arepredictivedrivestockmarketvaluesasmuchasnews.ThisissupportedofchangesinDJIAclosingvalues.Ourresultsindicatethatthebyrecentresearchby[10]whoextractan
