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1、StrategiesforCrowdsourcingSocialDataAnalysisWesleyWillett?,JeffreyHeer†,ManeeshAgrawala??ComputerScienceDivision,UniversityofCalifornia,Berkeleyfwillettw,maneeshg@cs.berkeley.edu†ComputerScienceDepartment,StanfordUniversityjheer@cs.stanford.eduABSTRACTelicitinghigh
2、-qualityexplanationsofthedatarequiresseed-Web-basedsocialdataanalysistoolsthatrelyonpublicdis-ingthediscussionwithprompts,examples,andotherstartingcussiontoproducehypothesesorexplanationsofpatternspointstoencouragecontributions[8,32].andtrendsindatararelyyieldhigh-
3、qualityresultsinprac-Outsidethelab,inreal-worldweb-baseddeployments,thetice.Crowdsourcingoffersanalternativeapproachinwhichvastmajorityofthevisualizationsinthesesocialdataanal-ananalystpaysworkerstogeneratesuchexplanations.Yet,ysistoolsyieldverylittlediscussion.Eve
4、nfewervisualiza-askingworkerswithvaryingskills,backgroundsandmoti-tionselicithigh-qualityanalyticalexplanationsthatareclear,vationstosimply“Explainwhyachartisinteresting”canplausible,andrelevanttoaparticularanalysisquestion.resultinirrelevant,unclearorspeculativeex
5、planationsofvariablequality.Toaddresstheseproblems,wecontributeWerecentlysurveyedtheManyEyeswebsiteandfoundthatsevenstrategiesforimprovingthequalityanddiversityoffrom2006to2010,userspublished162,282datasetsbutworker-generatedexplanations.Ourexperimentsshowthatgener
6、atedonly77,984visualizationsandleftjust15,464com-using(S1)feature-orientedprompts,providing(S2)goodex-ments.Wethenrandomlysampled100ofthevisualizationsamples,andincluding(S3)referencegathering,(S4)chartcontainingcommentsandfoundthatjust11%ofthecom-reading,and(S5)an
7、notationsubtasksincreasesthequalitymentsincludedaplausiblehypothesisorexplanationfortheofresponsesby28%forUSworkersand196%fornon-datainthechart.Thelowlevelofcommentingmayrepre-USworkers.Feature-orientedpromptsimproveexplanationsentashortageofviewersormaybeduetolurk
8、ing–acom-qualityby69%to236%dependingontheprompt.Wealsomonwebphenomenoninwhichvisitorsexploreandreadshowthat(S6)pre-annotatingchartscanfocusworker