vera data week preso and script

Sara VeraSenior Data Analyst at Causes.com

[email protected]

The Data Science of Collective Action

Online Virality vs Real-World Impact

http://oxfammonashpartnership.wordpress.com

Sortable: http://sortable.com/blog/rise-of-the-slacktivist/

http://atlanticsentinel.com/2012/

In this presentation

• For whom are we building this product?

• Where does Causes data come from?

• How do we use data to inspire civic action?

• How do we use data to measure impact?

Step One: Who are our users?

Good Ol’ Clustering• Quantitative Methods

• K-means clustering

• Decision Trees

• Qualitative Methods

• Surveys

• Interviews

K-means Clusters

Decision Trees

Surveys and Interviews

• Understand how people use Causes.com

• What inspired you to use Causes?

• Learn about campaign activity beyond Causes’ website

• How active are your friends in protests, petitions, boycotts?

• Learn as much as possible about a wide range of topics

Results: Six User Personas

Now, the next iteration of data

collection

We know who’s using our site.

Where does our data come from?

• Demographic Profiles

• Campaign Interests

• Supporter Network

• Online Behavior

First step to civic engagement:

• Connect with your ‘friends,’ ‘followers’ and ‘connections’!

• Support this cause you care about!

• Follow this issue you’re interested in!

• Support the people who share your values!

Recommendation Engines!

What about measuring impact?

Theory of ChangeCausal Logic behind intervention

Inputs

Activities

Outputs

Outcomes

Impacts

What happens

What goes in

Immediate Results

Med-term Results

Long-term Results

Abrahim & Rangan 2010

Outcome of NBC Petition

• NRA loses an advertising platform

• Animal Conservation awareness

• 107K are ready to mobilize

Data and Impact

2. Tools3. Short-term Results

1. Data

4. Long-term Impact

... And back to the beginning!

Thank [email protected]

SaraVera.10/3/2013.DataWeekTalk

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TheDataScienceofCollectiveAction:OnlineViralityversusReal-WorldImpact[SLIDEIntro]Hi,mynameisSaraVeraandIamaSeniorDataAnalystatCauses.com.Causesistheworld’slargestcampaigningplatform.Weconnectpeoplewhosupportacommoncauseandempowerthemtotakeactiontogether.InSeptember,CauseslaunchedtheSupporterNetwork,anindependentnetworkthatconnectsideologicallyalignedindividuals,celebrities,nonprofitorganizationsandsociallyresponsiblebrandsaroundtheworldtoinspirecollectiveaction.Campaigningisdependentonnetworkingandpeer-to-peerinfluence.TheInternetcouldbethegreatestorganizingtoolhumanityhasdevised,connectingpeoplefromallpartsoftheglobeandincreasingthefeelingthatanindividualisabletomobilizeagrouptoaccomplishgroup-basedgoals,which,incollectiveactionliterature,iscalledperceivedefficacy.We’veseenglimmers[ArabSpringSLIDE]oftheInternet’spotentialtofacilitatecollectiveactioninmovementsliketheArabSpring.AtCauses,thedatawecollectmakesitpossibleforustodeliverthebestcampaigningtoolssuitedtoorganizers’needs.Today,Iwilldiscussthedatascienceofcollectiveactionandhowweusedatatoinformaproductthattransforms[SLIDEaboutslacktivisim]“Slacktivism”toActivism.Slacktivism--forthoseofyouwhodon’tknow--isatermtodescribeclickingbuttonstofeellikeyou’remakingadifferenceintheworld.Whiletheterm“slacktivist”makesitsoundlikeonlineactivismisafeeblepretenseformakingadifference,inreality,leveragingonlinetoolstomaximizeviralityandgetamessagebeyond“thechoir”isquitepowerful.Further,accordingtoSortable,“slacktivists”aretwiceaslikelyasthegeneralpopulationtovolunteer,takepartinanevent,andaskfordonations.Whatiforganizerscouldbettermobilizetheseonlineactivists?Onlinenetworkshelpusleveragepeer-to-peerinfluenceandgivepowertothecollectivevoice.[SLIDEObamacampaign]Evenifyoudon’tloveBarackObama,youcan’tdenythathesqueezedeveryinsightandactionoutoftechnologyanddatatomakeasuccessfulbidforthepresidency.[CAUSESSLIDE]Howcanpeopleoptimizetheircampaignsandgrowacampaigntoscalewithoutthetoolsandknowledgeofcontentmarketers?Theansweris-ourtoolshelppeopleachievethisbecausetheyarebuilttoleverageback-enddatathathelpsensuretherightcampaignisputinfrontoftherightperson,attherighttime.[SLIDEInthispresentation]Inthispresentation,Iwillanswer:

1. Whoarewebuildingthisfor?2. WheredoesCausesdatacomefrom?3. Howdoweusedatatoinspirecollectiveaction?4. Andhowdowemeasureimpact?


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Inansweringthesequestions,Iwillhelpdefinehowtoday’sonlineinfluencersareusingtoday’stechnologytobetterorganizearoundcommoncausesandcampaignsforreal-worldchange.[SLIDEWhoareourusers]AtCauses,ourfirstmissionistogetpeoplecivicallyengaged.Weunderstandthattomakeareal-worldimpact,inspiringactioniskey.Theseactionsareeverythingfromreadingandsharingcontenttostartingagrassrootscampaign.[GoodOl’ClusteringSLIDE]Butfirst,togetpeopleinvolved,weneedtounderstandwhotheyare.WhenwesetouttobuildtheSupporterNetwork,westartedbyperformingaclusteranalysisofourexistinguserstoinformthedirectionthatourproductwouldtake.Forthisresearch,wesubsetourdatato200,000userswhousedCausesbetweenJuneandDecember2012.From230variables,wederived30predictivevariablesbywhichtostartcategorizingourusers,suchasage,income,education,theiractivitylevelandtopicalcampaigninterests.Werank-meansclusteringalgorithmonourentiredataset,whichresultedin6distinctpersonalitytypes.[K-meansSLIDE]Thisisavisualizationofourclusteringwork.Oneofourgroupsisexcludedbecauseitisessentiallyasmall“other”categoryofpeoplewhodon’treallyfitintoanyonecluster.Youcanseethatthebottomtwoclustersontheslideexhibitdrasticallydifferentbehaviorthanthetopthreeclusters--that'swhythey're"farther"away.Whileit'shardtogaugewhatdistanceslikethisreallymean,butit’saninformativevisualizationofwhatouruserbaselookslike.Afterperformingthek-meansclusteranalysistofigureoutwhobelongsinwhichcluster,weusedthese6clusterstotrainthe[RandomForestSLIDE]randomforestmodeltofindouthowpredictiveeachvariableisinidentifyingwhichclustersomeonebelongsto.Usingtherandomforestmodel,wefound30variablesthatbestpredicteduserclassification.[SurveyandInterviewSLIDE]Usingthebehavioralanddemographictrendswesawthroughourmachinelearningclassification,wedugdeeperintothemotivationsofourusersthroughsurveysandinterviews.Wereceivedalmost1,500responsestoour20questionsurvey.[ResultsSLIDE]98%ofourusersfitintooneoftheseonlineactivistpersonas.“Theambitiousactivist”isinhismid-forties,andhe’spassionate,talkative,andenthusiasticaboutsharinghisnewfoundpassionforcreatingimpactintheworldwithasmanypeopleaspossible.


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“Thepracticalactivist”isinhislatethirties,hehasfocusedideasabouthowhecanbestaffectchangeintheworldandheseekstofindasoapboxwherehecansharehisideaswithanaudience.SiteslikeCausesaresupplementstohisofflineactivism,notasubstitute.“Theself-assuredmillennial”isinhismid-twenties.Heisself-confidentandbelievesthathecanplayanintegralpartinchangingtheworldaroundhim.Butitcanbedifficultforhimtopledgeallegiancetojustonecampaignororganizationbecauseifheseesinjustice,hewantstogetinvolved,nomatterthecontext.“Theorganizedretiree”hasrecentlyretiredafterherasuccessfulcareerandisnotreadytoslowdown.Asapracticedorganizer,sheapproachesherworkmethodically:sheresearcheslegislation,educatesherselfandstaysactivethroughleadershiprolesinlocalorganizations.Although“Thetenaciousveteranactivist”isretiredandhasacouplehealthproblemsthatkeephermostlyhomebound,herenthusiasmforchangeisasprevalentasever.She’sbeeninvolvedincampaignsforsocialchangethroughoutherlife;alackofmobilityhasdrivenhertoparticipatenowonline.Andwhile“Thecasualparticipant”wouldbynomeansidentifyherselfasanactivist,shedoesrecognizetheflawsandfrustrationsintheworldaroundher.ShevisitssiteslikeCausesthroughinvitationsfromherfriends,butdoesnotfeelmuchloyaltytothecampaignsinwhichsheparticipates.[SLIDENextiterationofdatacollection]Onceweunderstoodourusers,weusedthedatatoinformtoolsthatwouldhelpconnectusersandinspirepeer-to-peersharing.Justlikeafieldofficeaskspeopletoknockon100doors,ormake100calls,weusedourdatatobuildaSupporterNetworkthatwoulddistributethecampaignresponsibilitiesbyconnecting“thecasualparticipant”with“thetenaciousveteranactivist”whoshareapassionforhealtheducationortheselfassuredmillennialwiththeorganizedretireewhoareconcernedwithenvironmentalconservation.Sohowdoweknowwhatthesepeoplecareabout?[SLIDE]Wheredoesourdatacomefrom?ThereareseveralcomponentstotheCauseswebsitewherewegathermostofourdata.Wecollectdemographicdatafromprofilepagesandcampaignpages,andwecollectalotofbehavioraldatawhenauserclicksorperformsanactiononoursite.Wealsohavealotofofflinedatathatwegetfrominterviewingandsurveyingourusers.HerearesomeexamplesofProfileandCampaignpagestogiveyousenseoftheinformationthatfromthemthatwecanuse.


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ProfilespagesandCampaigns:[SLIDEofmypersonalprofile]HereismyPersonalProfilepage.YoucanseethatIhavedisplayedmycivicidentitybychoosingvirtualbumperstickers.EachstickerrepresentsanissuethatIcareabout,butisalsoapieceofdatathatweuseatCausestomakedecisionsaboutourproductandthebestwaywecanfacilitatesupporterconnectionsandcampaignsuccess.Overhere,youcanseewhomIsupportandwhosupportsme.Supportingbasicallymeans,“Hey,Ilikewhatyoustandfor,letmeknowhowIcanhelp.”Whoyousupportismeanttobeveryintentional.Usingthesupporternetwork--individuals,nonprofitsandbrandscanreachaninterestedaudienceanddrawattentiontospecificissuesandcampaigns.Wealsousethesupporternetworktoanalyzedemographicsrelatedtocampaigning,fundraising,andpoliticalaffiliations.[BrandSLIDE]Brandand[OrgSLIDE]Organizationprofilepagesareasimilarsetup.Whenanorganizercreatesacampaign,theyhavetheoptionof“tagging”thecampaignwithrelevantissuecategoriessopeoplecaneasilysearchforit.[SierraClubCampaignPage]Forexample,SierraClubcampaignsmightbetaggedwith‘conservation,’‘environment,’andmoredescriptive,specifictagsdependingonthecampaign,suchas‘oilandgasconservation.’ThistaggingsystemalsoallowsusatCausestocategorizethecampaignsonourwebsiteinto“issue”pagesinordertosurfacerelevantcontenttoourusers.Itisalsopossibletopostcomments,storiesandphotos,givingpeopleawaytobecomemoreengagedandpersonallyinvolved.[TonySLIDE]Andfinally,wehaveanexampleofapersonalcampaignpage,whichisawayforasupportertobiteoffasmallerpieceofalargercampaigntomaketheoverallgoalmoretangible.Tonyiscollecting10signaturesforalargercampaignthatiscollectingatotalof100signaturesforapetitiontomakeNorthBeachsidewalksmorepedestrianfriendly.IfTonyinvitesyoutosignthispetition,youcanclickbacktothe`overallcampaigntoreadmoreabouttheSanFranciscoCountyTransportationAuthority,theneighborhoodstudiesbeingconductedandotherspecificbackgroundinformationregardingthispetition.SoIjustwalkedyouthroughhowpeoplesetuptheircivicidentity,createasupporternetwork,andtakeactiononcampaignstheycareabout.Fromhere,weusethisinformationtomakethisprocessmoreefficientandengaging.[SLIDERecommendationEngines]Somewouldsayyouneedheartandpassionbuthere,weneedDiscovery!Discoveryisahugefirststeptoengagingourusers.Andwithalloftheinformationweseeontheprofilepages,thevirtualbumperstickers,campaignissuetags,andbehavioraldata,wetrytosurfacerelevantcontentandhelpusersdeterminewhointheirexistingonlinenetworksonFacebook,LinkedInandTwitterarelikelytosharetheircampaigninterests.


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Whileusersarebuildingtheirsupporternetworksandtakingaction,wecontinuetorefineandsuggestsupporter-connections,issuesyoumightfindinteresting,andinspireyoutotakeaction.Thisleadstotheobviousquestionofassessingwhetheryouractionshaveanimpactintherealworld.[SLIDE]MeasuringImpactMeasuringimpactisaperennialproblemfororganizationsinvestedinsocialchange.It’shardenoughtodefineimpact,letalonefigureoutmetricstokeeptrackof.PeopleneedtofeelthattakingactiononlineisamorerewardingexperiencethansendingatweetorpostingonFacebook.Ifsomeonestartsorparticipatesinacampaign,isthereareturnontheirinvestment?Canweuseourdatatoshowtheimpactofthesecampaigns?[SLIDETheoryofChange]TherehasbeensomeresearchfromtheHarvardBusinessSchoolabouthowtomeasureimpact.Inthislineofresearch,theauthorsoutlineacontingencyframeworkformeasuringresultsbasedonthecausallogicofchangethatunderliesanyinterventionprogram.Thelogicchainincludesanorganization’sInputsandActivitiesthatleadtooutputs,outcomes,andultimately,impact.Inputsincludefunds,equipmentandsupplies,knowledgeandtechnicalexpertiseActivitiesincludebasicneedsdelivered,suchasfoodandshelter;orservicesdelivered,suchastrainingprogramsOutputs,aretheimmediateresultsOutcomesarethemedium-termresultssuchasimprovedlivingconditionsandhealth,increasedincomes,andenhancedpoliticalvoiceAndImpactsarelong-termresultsthatindicatefundamentalchangesinsocialnormsDecidingwhattomeasuredependsonwhereinthelogicchainyourcompanyorgrouplands.Giventhediversemissionandcapacitiesofcompaniesandorganizations,someshouldbemonitoringlong-termimpacts,whileothersshouldsticktoreportingimmediateresults.


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AtCausestoday,[CausalLogicSLIDE]wehavedatatomeasureshort-termoutcomesinthefirsthalfofthislogicchain.Wekeeptrackofmoneyraised,petitionssignedandothershorter-termoutcomesofcampaignsthatoursitefacilitates.Here’sanexample.[ElephantSLIDE]YoumayhaveheardthecontroversyoveranNRA-sponsoredhuntingshowontheNBCSportsNetworklastweek.TheleaderofthiscampaignwasoutragedwhenhesawanNRAlobbyistshootathreatenedbullelephantinthefaceon“UnderWildSkies”.TheleaderofthiscampaignoriginallycreatedapetitiontoNBCtostopairingthisepisodetoanationalaudience.Heasked,“DothevaluesofNBCreallyfallinlinewiththistypeofprogrammingwhereendangeredanimalsarehunteddownbytheworld’sleadingpro-gunlobby?”Thisleaderwasabletouseoursupporternetworktoidentifyalargeofgroupofpeopleconcernedwithanimalrights,makingparticipationandsharingratesforthepetitionveryhigh.Thisispartofgettingtherightcontentinfrontoftherightpeople,attherighttime.[PersonalCampaignsSLIDE]Themomentumreallygotgoingwhen639Personalcampaignswerestartedtohelptheleaderreachhisoverallgoalof100,000signatures.Here,thetransitionfromclickingtocreatingisthedifferencebetweenslacktivismandonlineactivism.Then,[KirstinDavisSLIDE]glamorouscelebritieslikeKirstinDavisfromSexandtheCitystartedre-tweetingthepetition,then[MediaSLIDES]theLATimes,HuffingtonPostandothermediaoutletspickedupthestory,increasingpublicpressure.[ElephantSLIDE]Intheend,thecollectiveinfluenceofover115,000peoplehelpedtopressureNBCtocanceltheprogram.Thisishowonlineactioncanbemoreeffectivethanactualfeethittingthepavement.Participationisdemocratizedinawaythatinspiresover100,000peopletosignapetitionwithin4days.Asusersseethenumberofpeopleinvolvedincreasing,theyareevenmoreinspiredtoact.Digitizingourcivicengagementallowseveryonetogetinvolvedandsay,“Hey,Istandbehindthiscause.”[LogicChainSLIDE]So,again,atCauses,hereweareinthefirstpartofthelogicchainwhereweseetheimmediateresultofthispetition--cancellingthisNRA-sponsoredtelevisionshow.Wecanleverageanddisplaysuccessbyshowinghowmanypeoplehavesignedthepetitionandcreatedtheirownpersonalcampaignstobiteoffapieceofthelargergoal.Butthisdoesn’tmeasurethelong-termimpact.


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[OutcomesSLIDE]Thereareseveraloutcomesofthiscampaign.Causeswasabletoconnectanimalrightsadvocatesconcernedwiththebrutalityofthehuntinwhichtheelephantisnotimmediatelykilled,aswellasguncontroladvocateswhoquestionedthepromotingofanNRA-sponsoredprogramtoanationalaudience.Inadditiontogettingsignatures,thecampaignpagesallowedsupporterstocollaborateandhelpedtoraiseawarenessandrecruitadditionalsupport.Butinthefuture,we’dliketosaythatthispetitioncontributedtoanoverallsocietalchangeinvalues.[DataandImpactSLIDE]Theselonger-termoutcomesarebothchallengingandexcitingfordatascientists.Theabilitytousedataaboutwhowearebuildingfortocreatetoolsforshort-termresultsisapromisingstarttomeasuringlong-termimpact.Weneedtofigureoutindicatorsofsocietalchangethatwecanmeasure,andtakenoteofhowmanycampaignsofwhattypesandvolumeandfrequencyittakesbeforewereachsomethresholdof“change.”Itaboutmakesmyheadexplodejustthinkingaboutit!But...Themorewecanshapeandrefinestrategybasedonpeople’sbehaviorandpractices,themorelikelywewillhavelastingimpact.[THANKYOUSLIDE]

vera data week preso and script

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