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1、ModelingfirstimpressionsfromhighlyvariablePNASPLUSfacialimages1RichardJ.W.Vernon,ClareA.M.Sutherland,AndrewW.Young,andTomHartleyDepartmentofPsychology,UniversityofYork,Heslington,YorkYO105DD,UnitedKingdomEditedbySusanT.Fiske,PrincetonUniversity,Princeton,NJ,andapprove
2、dJuly7,2014(receivedforreviewMay27,2014)Firstimpressionsofsocialtraits,suchastrustworthinessorhaveotherimmaturecharacteristicsbasedona“babyfaced”dominance,arereliablyperceivedinfaces,anddespitetheirappearance(16).Exploringthisgeneralapproachofseekingthequestionableval
3、iditytheycanhaveconsiderablereal-worldcon-factorsthatmightunderliefacialfirstimpressions,Oosterhofsequences.WesoughttouncovertheinformationdrivingsuchandTodorov(17)foundthatarangeoftraitratingsactuallyseemjudgments,usinganattribute-basedapproach.Attributes(physi-toref
4、lectjudgmentsalongtwonear-orthogonaldimensions:calfacialfeatures)wereobjectivelymeasuredfromfeaturetrustworthiness(valence)anddominance.Thetrustworthinesspositionsandcolorsinadatabaseofhighlyvariable“ambient”dimensionappearedtorelyheavilyonangriness-to-happinessfaceph
5、otographs,andthenusedasinputforaneuralnetworkcues,whereasdominanceappearedtoreflectfacialmaturityortomodelfactordimensions(approachability,youthful-attractive-masculinity.Theuseofsuchcuesbyhumanperceiverscanbeness,anddominance)thoughttounderliesocialattributions.Avery
6、subtle;evensupposedlyneutralfacescanhaveastructurallinearmodelbasedonthisapproachwasabletoaccountforresemblancetoemotionalexpressionsthatcanguidetrait58%ofthevarianceinraters’impressionsofpreviouslyunseenjudgments(18).faces,andfactor-attributecorrelationscouldbeusedto
7、rankOosterhofandTodorov’s(17)findingsimplythattraitjudg-attributesbytheirimportancetoeachfactor.Reversingthispro-mentsarelikelytobebaseduponbothstable(e.g.,masculinity)cess,neuralnetworkswerethenusedtopredictfacialattributesandmoretransient(e.g.,smiling)physicalproper
8、ties(“attrib-andcorrespondingimagepropertiesfromspecificcombinationsofutes”)ofanindividual’sface.However,thetraitratingsthey
