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TheRoleofSocialMediaandAr2ficialIntelligenceforDisasterResponse
MuhammadImranQatarCompu+ngResearchIns+tute
HamadBinKhalifaUniversityDoha,Qatar
May25,2016
h<p://mimran.me/
Fromtradi*onaltoemergingtoolsforcrisisresponse
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ThisTalkisAbout…• TheRoleofInforma2oninTime-cri2calSitua2ons
– Naturaldisastersandtheirdestruc+ons– Man-madedisastersandmassconvergenceevents
• TheRoleofSocialMediaforDisasterResponse– Par+cularfocusonmicro-bloggingplaJorms– Availabilityofvarioustypesofinforma+onandopportuni+es
• TheRoleofAr2ficialIntelligenceforDisasterResponse– HowAIisusefulindisasterresponse– VariousAItechniques,approaches,andtools– Workofcrisiscompu+nggroupatQCRI– Ongoingresearch– Futuredirec+ons
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Source:UNISDR
MostAffectedCountriesbyNaturalDisasters(1995-2015)
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HumansSufferingandEconomicDamagebyDisasters
Humanssufferingfromtheimpactsofdisasters,crises,andarmedconflict
Millionsofpeopleaffectedeachyearbydisasters;Atanannualcosttotheglobaleconomythatexceeds$300billion
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PlanandPrepare
Humanssufferingfromtheimpactsofdisasters,crises,andarmedconflict
Millionsofpeopleaffectedeachyearbydisasters;Atanannualcosttotheglobaleconomythatexceeds$300billion
Disastersareunavoidablebutplanningcanlessen
theireffects
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PlanandPrepare
Humanssufferingfromtheimpactsofdisasters,crises,andarmedconflict
Millionsofpeopleaffectedeachyearbydisasters;Atanannualcosttotheglobaleconomythatexceeds$300billion
Providehelpinghand…
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- Between2008and2014,184millionpeopledisplacedbynaturaldisasters
- Over60millionduetoconflicts
- Anaverage26.4millioneachyear
TheUrgencytoActandPlan
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Informa2on:ALifelineDuringDisasters
Theopaquenessinducedbydisastersisoverwhelming
Peopleneedinforma2onasmuchaswater,food,medicineorshelter
Lackofinforma+oncanmakepeoplevic2msofdisasterandtargetsofaid
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DataorDialogue?TheRoleofInforma2oninDisasters
IainLogan,formerheadofdisasteropera+ons,Interna+onalFedera+on:“Theveryfirstthingyouneedtodoisclimbintoahelicopter.Youcan’tgettoseehowmanypeopleareburiedbutyougetaneagle’seyeview…Youcanseewhichairfieldsareworking,whichbridgesaredown.Aderthreetofourhoursinahelicopter,Ihadacompleteoverviewofthegeographicalextentofthedisaster(earthquakeinElSalvador,2001),thelogis+csinvolved,thepopula+oncenters–alsowherenottosendpeople.Thenyoumustgetonthegroundtogetthequality.”
-Informa+onBestowsPower-
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TheRoleofSocialMedia
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SocialMediaUseDuringChristchurchEarthquake
Aself-organizedworkforceof10,000volunteersgatheredonFacebook
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TheRoleofTwi<erDuringThailandFloods
[AlisaKongthonetal.2011]
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Twi<erBreaksEventsFasterFirstreport
Breaksthestory33minutesbeforelocalTV
HudsonPlaneCrash
WestgateMallA<ack
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Twi<erBreaksEventsFasterFirstreportonTwi<er Aaer1minute
Aaer2minutes
BostonBombing
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CrisisCommunica2onsBeforeandNow
GeraldBaron
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AnalysisofTwi<erCrisis-RelatedDataAnIn-depthStudy
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Twi<erCrisis-RelatedData(2012)
Source:QatarCompu+ngResearchIns+tute-PublishedinWorldHumanitarianDataandTrends2014(UNOCHA)
Twioerdatafrom13crises;Analyzedover100,000tweets;Informa+ontypesandsources
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Twi<erCrisis-RelatedData(2013)
Source:QatarCompu+ngResearchIns+tute-PublishedinWorldHumanitarianDataandTrends2014(UNOCHA)
Twioerdatafrom13crises;Analyzedover100,000tweets;Informa+ontypesandsources
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Twi<erCrisis-RelatedData(All)
- Twioerdatafrom13recentcrises
- Over100,000tweets
- Informa2ontypes
- Typesofsources
Source:QatarCompu+ngResearchIns+tute-PublishedinWorldHumanitarianDataandTrends2014(UNOCHA)
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UNOCHAHumanitarianClusters-RelatedInforma2ononTwi<er
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TyphoonYolanda–OCHAClusters
- Performedanalysisof
morethan440,000tweetsduringthefirst48hours
- 15%ofthetweetsfoundpoten2allyrelevant
Source:QatarCompu+ngResearchIns+tute-PublishedinWorldHumanitarianDataandTrends2014(UNOCHA)
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TyphoonYolanda–OCHAClusters
Source:QatarCompu+ngResearchIns+tute-PublishedinWorldHumanitarianDataandTrends2014(UNOCHA)
- Performedanalysisof
morethan440,000tweetsduringthefirst48hours
- 15%ofthetweetsfoundpoten2allyrelevant
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SandyHurricaneTwi<erDataAnalysis
@NYGovCuomoordersclosingofNYCbridges.OnlyStatenIslandbridgesunaffectedatthis+me.Bridgesmustcloseby7pm.#Sandy#NYC.
rt@911buff:publichelpneeded:2boys2&4missingnearly24hoursadertheygotseparatedfromtheirmomwhencarsubmergedinsi.#sandy#911buff
freakingout.homealone.willjustwatchtv#Sandy#NYC.
400Volunteersareneededforareasthat#Sandydestroyed.
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@NYGovCuomoordersclosingofNYCbridges.OnlyStatenIslandbridgesunaffectedatthis+me.Bridgesmustcloseby7pm.#Sandy#NYC.
rt@911buff:publichelpneeded:2boys2&4missingnearly24hoursadertheygotseparatedfromtheirmomwhencarsubmergedinsi.#sandy#911buff
freakingout.homealone.willjustwatchtv#Sandy#NYC.
400Volunteersareneededforareasthat#Sandydestroyed.
Personal
Informa+ve
SandyHurricaneTwi<erDataAnalysis
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@NYGovCuomoordersclosingofNYCbridges.OnlyStatenIslandbridgesunaffectedatthis+me.Bridgesmustcloseby7pm.#Sandy#NYC.
rt@911buff:publichelpneeded:2boys2&4missingnearly24hoursadertheygotseparatedfromtheirmomwhencarsubmergedinsi.#sandy#911buff
freakingout.homealone.willjustwatchtv#Sandy#NYC.
400Volunteersareneededforareasthat#Sandydestroyed.
Personal
Informa+ve
Cau+onandAdvice
Casual+esandDamage
Dona+ons
SandyHurricaneTwi<erDataAnalysis
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@NYGovCuomoordersclosingofNYCbridges.OnlyStatenIslandbridgesunaffectedatthis+me.Bridgesmustcloseby7pm.#Sandy#NYC.
rt@911buff:publichelpneeded:2boys2&4missingnearly24hoursadertheygotseparatedfromtheirmomwhencarsubmergedinsi.#sandy#911buff
freakingout.homealone.willjustwatchtv#Sandy#NYC.
400Volunteersareneededforareasthat#Sandydestroyed.
Personal
Informa+ve
Cau+onandAdvice
Casual+esandDamage
Dona+ons
SandyHurricaneTwi<erDataAnalysis
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MERSOutbreakTwi<erDataAnalysis
MiddleEastRespiratorySyndrome(MERS)Twioerdatacollec+onfrom:2014-04-27to2014-07-14usinghashtag#MERS(Total=215,370)Dataanalysis:Reportsofsymptoms Affectedpeoplereports Deathreports
DiseasetransmissionreportsPreven+onques+ons Treatmentques+ons
Reportsofsignsorsymptomssuchasfever,coughorques+ons
ReportsofaffectedpeopleduetotheMERSdisease
ReportsofdeathsduetotheMERSdisease
Ques+onsorsugges+onsrelatedtothepreven+onofdisease
Reportsorques+onsrelatedtothetransmissionofthedisease
Ques+onsorsugges+onsregardingthetreatmentofthedisease
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SocialMediaDuringMERSOutbreak
RT@abeoel:TwoworkersatFLhospitalexposedtoapa+entwithMiddleEastRespiratorySyndromeareshowingflu-likesymptoms
Coronavirussymptomsinclude:fever,coughing,shortnessofbreath,conges2oninthenoseandthroat,andinsomecasesdiarrhea.MERS#MERSisarela+velynewrespiratoryillness,spreadb/wpeopleinclosecontact.Symptomsarefever,cough,&shortnessofbreath.SaudiArabiafindsanother32MERScasesasdiseasespreads:RIYADH(Reuters)-SaudiArabiasaidonThursday...hop://t.co/cPhm0uTRCo
Signsandsymptoms
Signsandsymptoms
Signsandsymptoms
Affectedindividuals
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SocialMediaDuringMERSOutbreak
FirstCaseofDeadlyMiddleEasternVirusFoundinU.S.:TheCentersforDiseaseControlhasconfirmedthatacaseofthedeadlyMidd...
ThirdCaseofMERSConfirmedintheU.S.:TheU.S.CentersforDiseaseControlandPreven+onconfirmedonSat...hop://t.co/Sb8PMyxVUnNocleartransmissionlinkbtwncamelsandhumansforMERS.94%Egyp+ancamelsseroposi+vebutnohumancasesyet.Hmm#asm2014Saudihealthauthori+esannouncedonMondaythatthedeathtollfromtheMERScoronavirushasreached115sincetherespiratorydisease...
Transmission
Deathreports
Affectedindividuals
Affectedindividuals
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ISCRAMCallforPapers
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AidisOutThere!
AiderisOutThere!
AIDRisAlsoOutThere!
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TheRoleofAr2ficialIntelligence
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2013PakistanEarthquakeSeptember28at07:34UTC
2010Hai2EarthquakeJanuary12at21:53UTC
DataandOpportuni2es
SocialMediaPlamorms
AvailabilityofImmenseData:
Around16thousandstweetsperminutewerepostedduringthehurricaneSandyintheUS.
Opportuni2es:- Earlywarningandeventdetec2on
- Situa2onalawareness
- Ac2onableinforma2on
- Rapidcrisisresponse- Post-disasteranalysis
Diseaseoutbreaks
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ProcessingSocialMediaData
Filter:removing,duplicates,spamandmessagesfrombots
Classify:categoriza+onofitemsintoinforma+ontypes
Cluster:iden+fytrendingandemergingtopic
Aggregate:makingsensebyconnec+ngdifferentpieces
Extract:shortsnippetsoffocusedinforma+on
Summarize:learningabiggerpictureofanevent
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WAIT!Beforeapplyinganytechnique?Please!Havealookatyourdatafirst
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DataCharacteris2csandPrepara2on
• Single-wordslangs:pls(please),srsly(seriously)• Mul2-wordslangs:imo(inmyopinion)• Misspellings:missin(missing),ovrcme(overcome)• Phone2csubs2tu2on:2morrow(tomorrow)• Wordwithoutspaces:prayfornepal(prayfornepal)
Canyouguess?“ruokm8”??
>>“AreyouOK,mate?”
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ToolstoProcessSocialMediaData
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SystemsforCrisis-RelevantDataProcessing
Twitris[PurohitandSheth2013]Twioer;seman+cenrichment,classifyautoma+cally,geotag
SensePlace2[MacEachrenetal.2011]Twioer;geotag,visualizeheat-mapsbasedongeotags
EMERSEEnhancedMessagingfortheEmergencyResponseSector[Carageaetal.2011]TwioerandSMS;machine-translate,classifyautoma+cally,alerts
ESAEmergencySitua+onAwareness[Yinetal.2012;Poweretal.2014]Twioer;detectbursts,classify,cluster,geotag
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SystemsforCrisis-RelevantDataProcessing
Twitcident[Abeletal.2012]TwioerandTwitPic;seman+cenrichment,classify
CrisisTracker[Rogstadiusetal.2013]Twioer;cluster,annotatemanually
Tweedr[Ashktorabetal.2014]Twioer;classifyautoma+cally,extractinforma+on,geotag
AIDR:Ar2ficialIntelligenceforDisasterResponse[Imranetal.2014a]Twioer;annotatemanually,classifyautoma+cally
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Ar2ficialIntelligenceforDisasterResponse
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Informa2onProcessing
Datacollec+on
1 2Humanannota+onsonsampledata
Machinetraining
3Classifica+on
4
DisasterTimeline:
DATACOLLECTION
Humansalonecannotprocesslargeamountsofdata,soweonlyusethemtohelpprocessasubset
Wetrainmachineusinghumaninputtoautoma+callyprocesslargeDataathighspeed
ForexampleusingKeywords,hashtagsetc.
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ImpactandResponseTimeline
DepartmentofCommunitySafety,QueenslandGovt.&UNOCHA,2011
Disasterresponse(today) Disasterresponse(ourtarget)
Requiresreal-2meprocessingofdata
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Datacollec+on
1 2Humanannota+ons Machinetraining
3Classifica+on
4
ONLINEAPPROACH
DATACOLLECTION
HA
Learning-1
CLASSIFICATIONOFDATA&DECISIONMAKINGPROCESS
Learning-2 Learning-3 … Learning-n
Humanannota+on-1
Humanannota+on-2
Humanannota+on-3 … Human
annota+on-n
Firstfewhours
Informa2onProcessing(Real-2me)
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BigChallenges–4Vs
• VolumeScaleofdata(20mtweetsin5daysTyphoonOklahoma)
• VelocityAnalysisofstreamingdata(16k/minduringSandy)
• VarietyDifferentforms/typesofdata(informa+ontypes)
• VeracityUncertaintyofdata
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MachineLearning+Crowdsourcing
hop://aidr.qcri.org/
AIDR=Machinelearning+Crowdsourcing
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CrowdsourcedStreamProcessingCombininghumanandmachinecomputa2on
Difficult, ambiguous items to be labeled by crowd
Automatic processing
Automatic processing
output output
Performing verification
Providing training data
a: Split automatic/manual processing b: Detect-verify paradigm
Automatic processing
Automatic processing output
c: Improving quality through active learning
input input
input
Difficult, ambiguous items to be labeled by crowd
Automatic processing
Automatic processing
output output
Performing verification
Providing training data
a: Split automatic/manual processing b: Detect-verify paradigm
Automatic processing
Automatic processing output
c: Improving quality through active learning
input input
input
Difficult, ambiguous items to be labeled by crowd
Automatic processing
Automatic processing
output output
Performing verification
Providing training data
a: Split automatic/manual processing b: Detect-verify paradigm
Automatic processing
Automatic processing output
c: Improving quality through active learning
input input
input
Qualityassuranceloops:humanprocessingelementsdothework,automa+cprocessingelementscheckforconsistencyProcess-verify:workisdoneautoma+cally,humanschecklow-confidenceorborderlinecasesOnlinesupervisedlearning:humanstrainmachinestoperformworkautoma+cally
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hop://aidr.qcri.org/
AIDR—Ar+ficialIntelligenceforDisasterResponse—isafree,open-source,andeasy-to-useplaJormtoautoma+callyfilterandclassifyrelevanttweetspostedduringhumanitariancrises.
1 2 3
Collect Curate Classify
AwardedtheGrandPrizeintheOpenSourceSoawareWorldChallenge2015
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AIDR:FromEnd-usersPerspec2ve
Collec2on Classifier(s)
• Keywords,hashtags• Geographicalboundingbox• Languages• Followspecificsetofusers
Acollec2onisasetoffilters Aclassifierisasetoftags• Dona2onsrequests&offers• Damage&causali2es• Eyewitnessaccounts• …
2stepsapproach1 2
hop://aidr.qcri.org/
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Real-2meClassifica2oninAIDR
hop://aidr.qcri.org/
Trainer
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AIDR–Collec2onSexngCollec2ondetaildashboard
hop://aidr.qcri.org/
GeographicalregionfilterLanguagefilter
Collec2ondefini2on
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hop://aidr.qcri.org/
AIDR–ClassifiersSexng
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AIDR–ClassifierSexng(cont.)
hop://aidr.qcri.org/
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HumanAnnota2oninAIDRInternalTaggingInterface
hop://aidr.qcri.org/
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HumanAnnota2onUsingMicroMappersMicroMapperInterface(webclicker)
hop://aidr.qcri.org/
Mobileclicker
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TaggedItemsandMachineOutput
hop://aidr.qcri.org/
Trainingexamples Classifiers’output
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High-levelArchitecture
hop://aidr.qcri.org/
Items Collector Feature Extractor Classifier(s)
Learner Crowdsourcing Task GeneratorStream of incoming
items from data sources
Item & featuresItem
An expert defines classifiers by givinga name and description for each category
Expert
Items
Crowd workers/volunteers
Model parameter
ClassifiedItem
A list of classified items by categoryand classifier’s confidence
Labelingtasks
Labeleditem
Datasource
Datasource
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Quality,Cost,andPerformanceofAIDR
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Qualityvs.CostinAIDR
hop://aidr.qcri.org/
Goal:Maximizingqualitywhileminimizingcost• Quality• classifica+onaccuracy• Precision
• Cost(humanlabels)• monetaryincaseofpaid-workers• +meincaseofvolunteers
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Qualityvs.CostinAIDR
hop://aidr.qcri.org/
Qualityvs.costusingpassivelearningandde-duplica2on
Qualityvs.costusingac2velearningandde-duplica2on
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Performance
hop://aidr.qcri.org/
Intermsofthroughputandlatency
Latencyoffeatureextractor,classifier,andthesystem
Throughputoffeatureextractor,classifier,andthesystem
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TyphoonHAGUPIT(2014)
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UNICEFU-ReportandAIDR-SMS
AItoAnswerHeathQueriesviaSMS
• EveryhourZambianyouthgetinfectedwithHIV/AIDS
• UNICEFlaunchedU-ReportprojectinZambia
• UsageofU-ReportplaJormhasrecentlyincreased300%
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UNICEFU-ReportinZambia
Manualprocessingandrou+ngofSMS
Counselors(expertsofHIV,STIs)
SMSservice
1 2
3
4
5
6
Vulnerablepeople
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UNICEFU-ReportinZambia+AIDR
Manualprocessingandrou+ngofSMS
Counselors(expertsofHIV,STIs)
SMSservice
1 2
3
4
5
6
Vulnerablepeople
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NewScien2stFeaturedThisWork
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MediaCoverage
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HumanAnnota2onSelec2onandschedulingforsupervisedclassifica2onsystem
OngoingWork
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HumanAnnota2on-Challenges
1-Labelingtaskselec2on• Whichtaskstopickforlabeling?• Noduplicatetasksshouldbelabeled• Priori2zetasksthatarelikelytoincreaseclassifier’saccuracy
Crowdsourcingisabigresearchtopic.Weaddresstwochallengeshere:
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Twi<erCrisesDatasets
1. Joplin-2011• Consistsof206,764tweetscollectedusing(#joplin)
2. Sandy-2012• Consistsof4,906,521tweetscollectedusing(#sandy,hurricanesandy,…)
3. Oklahoma-2013• Consistsof2,742,588tweetscollectedusing(Oklahoma,tornado,…)
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Distribu2onofTweetsintoPhases
Pre:preparednessphaseImpact:phasecorrespondstotheperiodinwhichthemaineffectsarefeltPost:correspondstoresponseandrecoveryphase
Joplin(led),Sandy(center),andOklahoma(right).Numberoftweetsperdayinalldatasets.
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LabelingTaskSelec2onExperiment:Isde-duplica2onnecessary?
Phase Train Phase Test AUC(withoutde-duplica2on)
AUC(withde-duplica2on)
S1(pre) 1,500 S1(pre) 500 0.78 0.74
S1(pre) 500 S1(pre) 500 0.73 0.72
S2(impact) 500 S2(impact) 500 0.80 0.72
S3(post) 500 S3(post) 500 0.79 0.73
S4(post’) 500 S4(post’) 500 0.70 0.64
• 29-74%oftweetsarere-tweets&60-75%arenearduplicates• Duplica+oncausesanar2ficialincreaseinaccuracy• Necessarytoreduceclassifierbias.Otherwiselearningonafewerconcepts• Necessarytoimproveworkersexperience
[Rogstadiusetal.2011]
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LabelingTaskSelec2onExperiment:Passivelearningvs.Ac2velearning
JOPLIN
SANDY
OKLAHOMA
S1 S2 S3 S4
AUCstabilizewithfewertrainingitemsusingac+velearning
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LabelingTaskScheduling
• All-at-oncelabeling• Obtain1,500labelsonS1anduseallfortraining
• Cumula2velabeling
• Obtain500labelsineachofS1,S2,andS3andtrainonlabelsavailableuptoeachphase
• Independentlabeling• Obtain500labelsineachofS1,S2,andS3andusethemostrecentlabelsfortraining,discardingold.
2-Labelingtaskscheduling
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LabelingTaskSchedulingExperiment:Whichlabelingstrategytofollow?
JOPLIN
SANDY
OKLAHOMA
Informa2ve Informa2ve(50%) Dona2ons
All-at-onceapproachdominatesininforma+veandcumula+vestrategyseemsbeoerfordona+ons
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DomainAdapta2onAbilityofasystemtoapplyknowledgeandskillslearnedinpreviousdomainstonoveldomains
OngoingWork
OurGoal:Tobuildasystemthatcanunderstandnaturallanguage
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DomainAdapta2onLabeledsource,butunlabeledtarget
Featureextractor
Machinelearningalgorithm
Featureextractor
Classifiermodel
Inputdocuments(bluedomain)Featurevectors
Labels
FeaturevectorsMachineclassifieditems
Inputdocuments(orangedomain)
Training
Predic2on
Sourceeventdata Targeteventdata
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SameDomainLearning
Trainingdata Machinelearningmodel Tes+ng
datainfer predict
Apples Apples
Apples
Oranges
Differentshapes,colors,skins,tastes,etc.
Sourcedomain Targetdomain
Oranges
Oranges
BUT
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Crisis-relatedDataClassifica2on
Trainingdata Machinelearningmodel Tes+ng
datainfer predict
ItalyearthquakeQueenslandfloodsSandyhurricane
CostaRicaearthquakeColoradofloodsTyphoonHaiyan
Differentevents,languages,needsetc.
Sourcedomain Targetdomain
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DomainAdapta2on
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ModelAdapta2onExperiments
• Modeladapta+onusingsinglesource– Usingboth:in-domainandcross-domain
• Modeladapta+onusingmul2plesources– In-domain– Mul+plesourceeventswithoutthetarget– Mul+plesourceeventswiththetarget
• Modeladapta+oninspecialcases– Samelanguages– Similarlanguages
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Observa2ons&Findings
• Datafromearlyhoursofacrisishelp• Pasteventsofsametypeareuseful• Samelanguagedataastargeteventisalsouseful• Similarlanguagesarealsouseful• Cross-domaintrainingdoesnotshowsignificantimprovements
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RapidCrisisResponseFutureDirec2ons
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ImageProcessingforDamageAssessment
Tasks• Imagecategoriza2on• E.g.building,bridge,roaddamage
• Damageandseverityassessment• Givenadamageimage,iden+fyseverityofdamage(low,mild,high)
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DeepLearningtoImproveClassifica2on
Tasks• Improvetextclassifica2onperformance• Availabilityofbigdata• Automa+cfeatureslearning• Binaryandmul+-classclassifica+on• Tes+ngdatafrommul+plepastevents
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TransferLearningDifferencesinclassifica2ontasks:• Differentclassifica+ontasks• Differenttypesofdisasters,stakeholders,informa+onneeds
Task:• Learnfromsourcetoclassifytarget• Seman+csimilaritybetweentasks• Instancessimilaritybetweendomains• Instanceweigh+ng
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Summariza2onandPriori2za2onofAc2onableInforma2on
Informa2onneeds&problem:
• Differentstakeholders• Differentgoals,requirements,andinfo.needs
Generalsitua2onalawarenessvs.Targetsitua2onalawareness• High-levelgeneralupdatesfromanevent• Specificupdates(infrastructuredamages)
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Resources,Datasets,AndTools
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TowardsStandardBaselinesandDatasets
CrisisNLP.qcri.org
- Accessto52milliontweets- Around50klabeledtweetsintohumanitariancategories- Largestword2vecembeddingstrainedon52mcrisis-relatedtweets- Out-of-vocabularydic2onaries
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TowardsStandardBaselinesandDatasets
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UpcomingBook
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DigitalHumanitarians:Book
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ACMCompu2ngSurvey
ProcessingSocialMediaMessagesinMassEmergency:ASurvey[Imranetal.2015]
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Conclusions• Informa2onbestowspowerfordisasterresponse
– Peopleneedinforma+onasmuchaswater,shelter,andfood– Disastersareunavoidable,butplanningcanlessentheireffects
• Socialmediaas2me-cri2calinforma2onsource– Earlywarnings,eventdetec+on,eventmonitoring– Availabilityofinforma+onopensnewopportuni+es
• Ar2ficialIntelligenceforDisasterResponse– Appliedresearchatitsbest– AI+humans-in-the-loopcanenablerapidcrisisresponse– AItechniquesusefulfor:
• Situa+onalawareness• Ac+onableinforma+onextrac+on• Summariza+on
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THANKYOU!h<p://mimran.me/
MuhammadImran
CrisisNLP.qcri.orgAIDR.qcri.org