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TheconsequencesofgenerativeAIforonlineknowledgecommunities
GordonBurtch,DokyunLee&ZhichenChen
Generativeartifcialintelligencetechnologies,especiallylargelanguagemodels(LLMs)likeChatGPT,arerevolutionizinginformationacquisitionandcontentproductionacrossavarietyofdomains.
Thesetechnologieshaveasignifcantpotentialtoimpactparticipationandcontentproduction
inonlineknowledgecommunities.Weprovideinitialevidenceofthis,analyzingdatafromStack
OverfowandRedditdevelopercommunitiesbetweenOctober2021andMarch2023,documentingChatGPT’sinfuenceonuseractivityintheformer.Weobservesignifcantdeclinesinbothwebsite
visitsandquestionvolumesatStackOverfow,particularlyaroundtopicswhereChatGPTexcels.Bycontrast,activityinRedditcommunitiesshowsnoevidenceofdecline,suggestingtheimportance
ofsocialfabricasabuferagainstthecommunity-degradingefectsofLLMs.Finally,thedeclinein
participationonStackOverfowisfoundtobeconcentratedamongnewerusers,indicatingthatmorejunior,lesssociallyembeddedusersareparticularlylikelytoexit.
Recentadvancementsingenerativeartifcialintelligence(GenAI)technologies,especiallylargelanguagemodels(LLMs)suchasChatGPT,havebeensignifcant.LLMsdemonstrateremarkableprofciencyintasksthatinvolveinformationretrievalandcontentcreation
1
–
3
.Giventhesecapabilities,itisimportanttoconsidertheirpotentialtodriveseismicshifsinthewayknowledgeisdevelopedandexchangedwithinonlineknowledgecommunities
4
,5
.
LLMsmaydrivebothpositiveandnegativeimpactsonparticipationandactivityatonlineknowledgecom-munities.Onthepositiveside,LLMscanenhanceknowledgesharingbyprovidingimmediate,relevantresponsestouserqueries,potentiallybolsteringcommunityengagementbyhelpinguserstoefcientlyaddressawiderrangeofpeerquestions.Viewedfromthisperspective,GenAItoolsmaycomplementandenhanceexistingactivitiesinacommunity,enablingagreatersupplyofinformation.Onthenegativeside,LLMsmayreplaceonlineknowledgecommunitiesaltogether.
Ifthedisplacementefectdominates,itwouldgiverisetoseveralseriousconcerns.First,whileLLMsoferinnovativesolutionsforinformationretrievalandcontentcreationandhavebeenshowntosignifcantlyenhanceindividualproductivityinavarietyofwritingandcodingtasks,theyhavealsobeenfoundtohallucinate,i.e.,providing‘confdentlyincorrect’responsestouserqueries
6
,andtoundermineworkerperformanceoncertaintypesoftasks
3
.Second,ifindividualparticipationinonlinecommunitiesweretodecline,thiswouldimplyadeclineinopportunitiesforallmannerofinterpersonalinteraction,uponwhichmanyimportantactivitiesdepend,e.g.,collaboration,mentorship,jobsearch.Further,totheextentasimilardynamicmayemergewithinformalorganizationsandworkcontexts,itwouldraisetheprospectofanalogousdeclinesinorganizationalattachment,peerlearning,careeradvancementandinnovation
7
–
12
.
Withtheaboveinmind,weaddresstwoquestionsinthiswork.First,weexaminetheefectsthatgenerativeartifcialintelligence(AI),particularlylargelanguagemodels(LLMs),haveonindividualengagementinonlineknowledgecommunities.Specifcally,weassesshowLLMsinfuenceuserparticipationandcontentcreationinonlineknowledgecommunities.Second,weexplorefactorsthatmoderate(amplifyorattenuate)theefectsofLLMsonparticipationandcontentcreationatonlineknowledgecommunities.Byaddressingtheserelationships,weaimtoadvanceourunderstandingoftheroleLLMsmayplayinshapingthefutureofknowledgesharingandcollaborationonline.Further,weseektoprovideinsightsintoapproachesandstrategiesthatcanencourageasustainableknowledgesharingdynamicbetweenhumanusersandAItechnologies.
WeevaluateourquestionsinthecontextofChatGPT’srelease,inlateNovemberof2022.Westartbyexam-ininghowthereleaseofChatGPTimpactedStackOverfow.WeshowthatChatGPT’sreleaseledtoamarkeddeclineinwebtrafctoStackOverfow,andacommensuratedeclineinquestionpostingvolumes.Wethenconsiderhowdeclinesinparticipationmayvaryacrosscommunitycontexts.LeveragingdataonpostingactivityinRedditdevelopercommunitiesoverthesameperiod,wehighlightanotablecontrast:nodetectibledeclinesinparticipation.Weattributethisdiferencetosocialfabric;whereasStockOverfowfocusesonpureinforma-tionexchange,Redditdevelopercommunitiesarecharacterizedbystrongersocialbonds.Further,consideringheterogeneityacrosstopicdomainswithinStackOverfow,weshowthatdeclinesinparticipationvariedgreatly
QuestromSchoolofBusiness,BostonUniversity,Boston,MA02215,USA.email:gburtch@
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dependingontheavailabilityofhistoricalcommunitydata,alikelyproxyforLLM’sabilitytoaddressques-tionsinadomain,giventhatdatawouldlikelyhavebeenusedintraining.Finally,weexplorewhichusersweremostafectedbyChatGPT’srelease,andtheimpactChatGPThashadonthecharacteristicsofcontentbeingposted.WeshowthatnewerusersweremostlikelytoexitthecommunityaferChatGPTwasreleased.Further,andrelatedly,weshowthatthequestionspostedtoStackOverfowbecamesystematicallymorecomplexandsophisticatedaferChatGPT’srelease.
Methods
Toaddressthesequestions,weleverageacombinationofdatasourcesandmethods(additionaldetailsarepro-videdinthesupplement).First,weemployaproprietarydatasetcapturingdailyaggregatecountsofvisitorsto,andalargesetofotherpopularwebsites.TisdatacoverstheperiodfromSeptember2022throughMarch2023.Additionally,weemploydataonthequestionsandanswerspostedtoStackOverfow,alongwithcharacteristicsofthepostingusers,fromtwocalendarperiodsthatcoverthesamespanofthecalendaryear.TetwosamplescoverOctober2021throughmid-Marchof2022,andOctober2022throughmid-Marchof2023.TesedatasetswereobtainedviatheStackExchangeDataExplorer,whichprovidesdownloadable,anonymizeddataonactivityindiferentStackExchangecommunities.Further,weemploydatafromsubred-,whichtracksaggregatedailycountsofpostingvolumestoeachsub-Reddit.Ourdatasourcesdonotincludeanypersonaluserinformation,andnoneofouranalysesmakeuseofanypersonaluserinformation. WefrstexaminedtheefectthatChatGPT’sreleaseonNovember30thof2022hadonwebtrafcarrivingatStackOverfow,leveragingthedailywebtrafcdataset.Tesample,sourcedfromSimilarWeb,includesdailytrafctothetop1000websites.Weemployavariantofthesyntheticcontrolmethod
13
,namelySyntheticControlUsingLASSO,orSCUL
14
.Takingthetimeseriesofwebvisitstoastreated,themethodidenti-fes,viaLASSO
15
,alinear,weightedcombinationofcandidatecontrolseries(websites)thatyieldsanaccuratepredictionoftrafctopriortoChatGPT’srelease.TeresultinglinearcombinationisthenusedtoimputeacounterfactualestimateoftrafcatintheperiodfollowingChatGPT’srelease,refectingpredictionsofwebtrafcvolumesthatwouldhavebeenobservedintheabsenceofChatGPT.
Second,weexaminedChatGPT’sefectsonthevolumeofquestionsbeingpostedtoStackOverfow.Weidentifedthetop50mostpopulartopictagsassociatedwithquestionsonStackOverfowduringourperiodofstudy,calculatingthedailycountofquestionsincludingeachtagoveratimewindowbracketingthedateofChatGPT’srelease.WethenfollowedtheapproachofRefs.
16
,
17
,constructingthesamesetoftopicpanelsforthesamecalendarperiod,oneyearprior,toserveasourcontrolwithinadiference-in-diferencesdesign,toestimateanaveragetreatmentefect,andtoenableevaluationbothoftheparalleltrendsassumption(whichissupportedbytheabsenceofsignifcantpre-treatmentdiferences)andtreatmentefectdynamics
18
.FigureS1inthesupplementprovidesavisualexplanationofourresearchdesign.
Tird,weconsideredwhethertheefectsmightdiferacrossonlineknowledgecommunities,dependingonthedegreetowhichacommunityisfocusedstrictlyoninformationexchange.Tatis,weconsideredthepotentialmitigatingefectofsocialfabric,i.e.socialbondsandconnections,asabuferagainstLLMsnegativeefectsonconnectionwithhumanpeers.TelogicforthistestisthatLLMs,despitebeingcapableofhigh-qualityinforma-tionprovisionaroundmanytopics,areoflessclearvalueasapuresubstituteforhumansocialconnections
19
.WethuscontrastedouraverageefectestimatesfromStackOverfowwithefectestimatesobtainedusingpanelsofdailypostingvolumesfromanalogoussub-communitiesatReddit(sub-Reddits),focusedonthesamesetsoftopics.RedditisausefulpointofcomparisonbecauseithasbeenwelldocumentedthatRedditdevelopercommunitiesarerelativelymoresocialandcommunalthanStackOverfow
20
,
21
.Wealsoexploredheterogene-ityintheStackOverfowefectsacrosstopics,repeatingourdiference-in-diferencesregressionforeachStackOverfowtopicandassociatedsub-reddit.
Lastly,weexploredshifsintheaveragecharacteristicsofusersandquestionsatStackOverfowfollowingChatGPT’srelease,specifcallyintermsofthepostingusers’accounttenure,indays,and,relatedly,theaveragecomplexityofpostedquestions.ItisreasonabletoexpectthattheindividualsmostlikelytorelyonChatGPTarejunior,newermembersofthecommunity,astheseindividualslikelyhavelesssocialattachmenttothecom-munity,andtheyarelikelytoaskrelativelysimplerquestions,whichChatGPTisbetterabletoaddress.Inturn,itisreasonabletoexpectthatthequestionsthatfailtobepostedarethosethatwouldhavebeenrelativelysimpler.Wetestedthesepossibilitiesintwoways,consideringquestion-leveldatafromStackOverfow.WebeganbyestimatingtheefectofChatGPT’sreleaseontheaveragetenure(indays)ofpostingusers’accounts.Next,weestimatedasimilarmodel,consideringtheaveragefrequencyof‘long’words(wordswith6ormorecharacters)withinpostedquestions,asaproxyforcomplexity.
Results
OverallimpactofLLMsoncommunityengagement
Figure
1
AdepictstheactualdailywebtrafctoStackOverfow(blue)alongsideourestimatesofthetrafcthatStackOverfowwouldhaveexperiencedintheabsenceofChatGPT’srelease(red).TeSyntheticControlesti-matescloselymirrorthetruetimeseriespriortoChatGPT’srelease,supportingtheirvalidityasacounterfactualforwhatwouldhaveoccurredpost.Figure
1
Bpresentsthediferencebetweenthesetimeseries.WeestimatethatStackOverfow’sdailywebtrafchasdeclinedbyapproximately1millionindividualsperday,equivalenttoapproximately12%ofthesite’sdailywebtrafcjustpriortoChatGPT’srelease.
LLMs’efectonusercontentproduction
Ourdiference-in-diferencesestimationsemployingdataonpostingactivityatStackOverfowrevealedthatquestionpostingvolumesper-topiconStackOverfowhavedeclinedmarkedlysinceChatGPT’srelease(Fig.
2
A).
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Figure1.Syntheticcontrolestimatesofdeclineindailywebtrafctostackoverfow.Estimatesareobtained
viasyntheticcontrolusingLASSO(SCUL),basedondailywebtrafcestimatesaccordingtoSimilarWebforthe1000mostpopularwebsitesontheinternet.Panel(A)depictstheactualwebtrafcvolumes(inblue)recordedbySimilarWebalongsidetheSyntheticControl(inred).Panel(B)depictsthediferencebetweenthetwoseries,refectingtheestimatedcausalefectofChatGPT.
Figure2.EstimatedefectsofChatGPTonuseractivityatstackoverfowandreddit.Estimatesareobtainedviadiference-in-diferencesregression,comparingcontentpostingvolumesoveraperiodbracketingtherelease
ofChatGPT(onNovember30th,2022)withawindowofequallengthobservedonecalendaryearprior.Panel
(A)depictsefectsovertime(byweek)onStackOverfowquestionvolumespertopic.Panel(B)depictsefectsonRedditpostingvolumes,persub-reddit,forsub-redditsdealingwithanoverlappingsetoftopics.Teshadedarearepresents95%confdenceintervals.
TisresultreinforcestheideathatLLMsarereplacingonlinecommunitiesasasourceofknowledgeformanyusers.RepeatingthesameanalysisusingRedditdata,weobservednoevidencethatChatGPThashadanyefectsonuserengagementatReddit(Fig.
2
B).WereplicatetheseresultsinFig.S2ofthesupplementemployingthematrixcompletionestimatorofRef.
22
.
HeterogeneityinChatGPT’sefectonstackoverfowpostingvolumesbytopic
WeobservedagreatdealofheterogeneityacrossStackOverfowtopics,yetconsistentlynullresultsacrosssub-reddits(Fig.
3
).Ourestimatesthusindicate,again,thatRedditdevelopercommunitieshavebeenlargelyunafectedbyChatGPT’srelease.OurStackOverfowresultsfurtherindicatethatthemostsubstantiallyafectedtopicsarethosemostheavilytiedtoconcrete,self-containedsofwarecodingactivities.Tatis,themostheav-ilyafectedtopicsarealsothosewherewemightanticipatethatChatGPTwouldperformquitewell,duetotheprevalenceofaccessibletrainingdata.
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Figure3.Topic-specifcefectsofChatGPTonstackoverfowandreddit.Estimatesareobtainedviadiference-in-diferencesregression,pertopic.Tefguredepictsefectestimatesforeachstackoverfowtopic(inorange)with95%confdenceintervalsandestimatesforeachsub-reddit(inred),whereavailable.Notethatdataon
sub-redditpostingvolumeswasnotavailableforthreesub-redditcommunities:javascript,jQuery,andDjango.OtherRedditestimatesareomittedduetothelackofaclearlyanalogoussub-redditaddressingthattopic.
Forexample,Python,CSS,Flutter,ReactJS,Django,SQL,Arrays,andPandasareallreferencestoprogram-minglanguages,specifcprogramminglibraries,ordatatypesandstructuresthatonemightencounterwhileworkingwithaprogramminglanguage.Incontrast,relativelyunafectedtagsappearmorelikelytorelatetotopicsinvolvingcomplextasks,requiringnotonlyappropriatesyntaxbutalsocontextualinformationthatwouldofenhavebeenoutsideofthescopeofChatGPT’strainingdata.Forexample,SpringandSpring-bootareJava-basedframeworksforenterprisesolutions,ofeninvolvingback-end(server-side)programminglogicwithprivateenterpriseknowledgebasesandsofwareinfrastructures.Questionsrelatedtothesetopicsareintuitivequestionsforwhichanautomated(i.e.cut-and-paste)solutionwouldbelessstraightforward,andlesslikelytoappearinthetextualtrainingdataavailablefortrainingtheLLM.AdditionalexampleshereincludethetagsrelatedtoAmazonWebServices,Firebase,Docker,SQLServer,andMicrosofAzure.
Toevaluatethispossibleexplanationmoredirectly,wecollecteddataonthevolumeofactiveGitHubreposi-toriesmakinguseofeachlanguageorframework,aswellasthenumberofindividualssubscribedtosub-redditsfocusedoneachlanguageorframework.WethenplottedascaledmeasureofeachvalueatoptheobservedefectsizesandobtainedFig.
4
.Tefgureindicatesaroughcorrelationbetweenavailablepublicsourcesoftrainingdataandourefectsizes.
ChatGPT’sefectonaverageuseraccountageandquestioncomplexity
Figure
5
depictsthechangeinaveragepostingusers’accounttenure,makingclearthat,uponChatGPT’srelease,asystematicrisebegantotakeplace,suchthatuserswereincreasinglylikelytobemoreestablished,olderaccounts.TeimplicationofthisresultisthatneweruseraccountsbecamesystematicallylesslikelytoparticipateintheStackOverfowcommunityaferChatGPTbecameavailable.Figure
6
depictstheefects,indicatingthatques-tionsexhibitedasystematicriseincomplexityfollowingthereleaseofChatGPT.
Tesefndings,consistentwiththeideathatmorejuniorandlessexperiencedusersbegantoexitmightbecauseforconcernifasimilardynamicisplayingoutinmoreformalorganizationandworkcontexts.Tisisbecausejuniorindividualsmaystandtolosethemostfromdeclinesinpeerinteraction—theseindividualstypi-callyaremoremarginalmembersoforganizationsandthushavelessrobustnetworksandhavethemosttoloseintermsofopportunitiesforcareeradvancement
23
.Further,theseindividualsmaybeleastcapableofrecognizingmistakesintheoutputofLLMs,whicharewellknowntoengageinhallucination,providing‘confdentlywrong’answerstouserqueries
6
.Indeed,recentworkobservesthatnon-expertsfacethegreatestdifcultydeterminingwhethertheinformationtheyhaveobtainedfromanLLMiscorrect
24
.
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Figure4.Topic-specifcefectsofChatGPTonstackoverfow(blackpointswith95%confdenceintervals)
withNumberofGithubrepositories(purple)andsub-redditsubscribers(red)overlaid.Weobservearough
correlationbetweenthevolumeofGithubrepositoriesmakinguseofagivenlanguageorframework,thelevelofactivityinassociatedsub-redditcommunities,andthemagnitudeofefectsizes.TisassociatesuggestsefectsarelargerfortopicswheremorepublicdatawasavailabletotraintheLLM.
Figure5.EfectofChatGPTreleaseontheaveragetenure(indays)ofuseraccountspostingquestionsto
stackoverfow.ShortlyaferChatGPT’srelease,weseeasystematicriseintheaverageage(indays)forthe
useraccountspostingquestionstoStackOverfow.Weseethataverageaccountagerisessystematicallyonce
ChatGPTisreleased,consistentwithneweraccountssystematicallyreducingtheirparticipationandexitingthecommunity.
Discussion
WehaveshownthatChatGPTsreleasewasassociatedwithadiscontinuousdeclineinwebtrafcandquestionpostingvolumesatStockOverfow.Tisresultisconsistentwiththeideathatmanyindividualsarenowrely-ingonLLMsforknowledgeacquisitioninlieuofhumanpeersinonlineknowledgecommunities.OurresultsdemonstratethattheseefectsmanifestedforStackOverfow,yetnotforRedditdevelopercommunities.
Further,wehaveshownthattheseefectsweremorepronouncedforverypopulartopicsascomparedtolesspopulartopics,andevidencesuggeststhatthisheterogeneityderivedfromthevolumeoftrainingdataavail-ableforLLMtrainingpriortoChatGPTsrelease.Finally,ourresultsdemonstratethatChatGPT’sreleasewas
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Figure6.EfectofChatGPT’sreleaseontheaveragecomplexityofquestionspostedtoStackOverfow,
refectedbytheaveragefrequencyof‘long’words(wordswith6ormorecharacters).ShortlyaferChatGPT’srelease,weseeasystematicriseintheaveragecomplexityofquestions.Tisresultisagainconsistentwiththeideathatneweraccountssystematicallyreducedtheirparticipationandexitedthecommunity.
associatedwithasignifcance,discontinuousincreaseintheaveragetenureofaccountsparticipatingonStackOverfow,andinthecomplexityofquestionsposted(asrefectedbytheprevalenceoflengthywordswithinquestions).Teseresultsareconsistentwiththeideathatthatnewer,lessexpertusersweremorelikelytobeginrelyingonChatGPTinlieuoftheonlineknowledgecommunity.
Ourfndingsbearseveralimportantimplicationsforthemanagementofonlineknowledgecommunities.Foronlinecommunities,ourfndingshighlighttheimportanceofsocialfabricasameansofensuringthesustain-abilityandsuccessofonlinecommunitiesintheageofgenerativeAI.OurfndingsthushighlightthatmanagersofonlineknowledgecommunitiescancombattheerodinginfuenceofLLMsbyenablingsocialization,asacomplementtopureinformationexchange.Ourfndingsalsohighlighthowcontentcharacteristicsandcom-munitymembershipcanshifbecauseofLLMs,observationsthatcaninformcommunitymanagerscontentmoderationstrategiesandtheiractivitiescenteredoncommunitygrowthandchurnprevention.
Beyondthepotentialconcernsaboutwhattheobserveddynamicsmayimplyforonlinecommunitiesandtheirmembers,ourfndingsalsoraiseimportantconcernsaboutthefutureofcontentproductioninonlinecommunities,whichbyallaccountshaveservedasakeysourceoftrainingdataformanyofthemostpopularLLMs,includingOpenAI’sGPT.Totheextentcontentproductiondeclinesintheseopencommunities,itwillreinforceconcernsthathavebeenraisedintheliteratureaboutlimitationsonthevolumeofdataavailableformodeltraining
25
.Ourfndingssuggestthatlong-termcontentlicensingagreementsthathaverecentlybeensignedbetweenLLMcreatorsandonlinecommunityoperatorsmaybeundermined.Iftheseissuesarelefunaddressed,thecontinuedadvancementofgenerativeAImodelsmaynecessitatethattheircreatorsidentifyalternativedatasources.
Conclusion
Ourworkisnotwithoutlimitations,someofwhichpresentopportunitiesforfutureresearch.First,forourresearchdesigntoyieldcausalinterpretations,wemustassumetheabsenceofconfoundedtreatments.Forexample,wereanotherlargeonlinecommunitytohaveemergedaroundthesametime,thepossibilityexiststhatitmayexplainthedeclineinparticipationatStackOverfow.Second,ourstudylacksanuancedanalysisofchangesincontentcharacteristics.Althoughwestudychangesinanswerqualityusingnetvotescores(seethesupplement),ourmeasuresmayrefectchangesinotheraspectsunrelatedtoinformationquality.Similarly,althoughwestudychangesinquestioncomplexity,ourmeasureofcomplexityistiedtowordlength.Futureworkcanthusrevisitthesequestionsemployingavarietyofothermeasuresofqualityandcomplexity.
Tird,althoughwehaveshownadeclineinparticipationatStackOverfow,weareunabletospeaktowhetherthesamedynamicisplayingoutinotherorganizationalsettings,e.g.workplaces.Itisalsoimportanttorecognizethatthecontextofouranalysesmaybeunique.TotheextentStackOverfowandRedditdevelopercommunitiesmightnotberepresentativeofdevelopercommunitiesmorebroadly,thegeneralizabilityoftheseresultswouldbeconstrained.Relatedly,itispossiblethattheresultsweobserveareuniquetoknowledgecommunitiesthatfocusonsofwaredevelopmentandinformationtechnology.Tedynamicsofcontentproductionmaydifermarkedlyinotherknowledgedomains.Finally,ourworkdemonstratesefectsoverarelativelyshortperiodoftime(severalmonths).Itispossiblethatthelonger-rundynamicsoftheobservedefectsmayshif.Giventhesepoints,futureworkcanandshouldendeavortoexplorethegeneralizabilityofourfndingstoothercommunities,andfutureworkshouldexaminethelonger-runefectsofgenerativeAItechnologiesoncommunityparticipa-tionandknowledgesharing.
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WeanticipatethatourstudywillinspiremoresophisticatedanalysesoftheefectsthatgenerativeAItechnolo-gies,includingLLMs,butalsogenerativeimage,audio,andvideomodels,mayhaveonpatternsofknowledgesharingandcollaborationwithinorganizationsandsocietymorebroadly.Suchworkiscruciallyneeded,tobetterunderstandthenuancesofwhereandwhenindividualsmayrelyonhumanpeersversusGenerativeAItools,andthedesirableandundesirableconsequencesfororganizationsandsociety,suchthatwecanbegintoplanforandmanagethisnewdynamic.
Dataavailability
DataonStackOverfowusers,questions,andanswerswasobtainedviatheStackExchangeDataExplorerat
/stackoverfow/query/new.
Dataonsub-redditpostingvolumeswasobtainedfrom
.SimilarWebdailywebtrafcdataisnotavailableforpublicdissemination,thoughitisavailableforpurchasefrom
https://deweydata.io
.StackOverfowdata,RedditdataandanalysisscriptsareavailableinapublicrepositoryattheOSF:
https://osf.io/qs6b3/
.
Received:23October2023;Accepted:2May2024
publishedonline:06May2024
References
1.Noy,S.&Zhang,W.Experimentalevidenceontheproductivityefectsofgenerativeartifcialintelligence.Science
/
10.2139/ssrn.4375283
(2023).
2.Peng,S.,Kalliamvakou,E.,Cihon,P.,Demirer,M.TeimpactofAIondeveloperproductivity:EvidencefromGithubcopilot.Preprintat
https://arX/2302.06590
(2023).
3.Dell-Acqua,F.etal.Navigatingthejaggedtechnologicalfrontier:FieldexperimentalevidenceoftheefectsofAIonknowledgeworkerproductivityandquality.HarvardBusinessSchoolWorkingPaper,no.24-013(2023).
4.Hwang,E.H.,Singh,P.V.&Argote,L.Knowledgesharinginonlinecommunities:Learningtocrossgeographicandhierarchicalboundaries.Organ.Sci.26(6),1593–1611(2015).
5.Hwang,E.H.&Krackhardt,D.Onlineknowledgecommunities:Breakingorsustainingknowledgesilos?.Prod.Oper.Manag.29(1),138–155(2020).
6.Bang,Y.etal.Amultitask,multilingual,multimodalevaluationofChatGPTonreasoning,hallucination,andinteractivity.InProc.ofthe13thInternationalJ
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