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WebsiteandSocialMediaAnalytics- ATextMiningApproach

YiluZhou,PhDAssociateProfessor

Gabelli SchoolofBusinessFordhamUniversity

The Text Mining Task Pyramid

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Case 1: Social Network and Content Analysis

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Who links to whom and who influences whom?How are the sites used?Which sites are more sophisticated?

YiluZhou,Jialun Qin,Hsinchun Chen,EdnaReid

MDS Visualization of Arab Group Web Sites

Hizb-Ut-Tahrir

Jihad Supporters

Palestinian supporters

Hizballah Cluster

Palestinian terrorists

Comparison - Content Analysis

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Black Separatists Christian Identity Militia Neo-confederates

Neo-Nazis/WhiteSupremacists

Eco-Terrorism

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aliz

ed C

onte

nt L

evel

s Communications

Fundraising

Ideology

Propaganda (insiders)

Propaganda (outsiders)

Virtual Community

Command and Control

Recruitment and Training

U.S. Domestic Extremist Web sites

Middle Eastern Extremist Web sites

00.10.20.30.40.50.60.70.80.91

Hizb-ut-Tahrir Hizbollah Al-Qaeda LinkedWebsites

Jihad Sympathizers Palestinian terroristgroups

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alize

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nten

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els Communications

Fundraising

Sharing Ideology

Propaganda (Insiders)

Propaganda(outsider)

Virtual Community

Command and Control

Recruitment and Training

Forum Content Analysis

Contents:

1- LinkstoterroristWebsites2- Messagesfromterroristgroups

3- Ideology4- Computerviruses

Yahoo! Group Name Description/Organization Content Language Postings after June 2004

Members Total postings

black_heart2010 · ( سرایاالموت للجھاد االلكتروني (Death Brigades of Electronic Jihad

Salafi Groups/ Al-QaedaRegistration required

1-2-3-4 Arabic 80 183 331

Jehaaadlast حي علىالجھاد في سبیل هللا

Salafi Groups/ Al-QaedaRegistration Not required

1-2-3 Arabic 235 436 494

mojahidon · المجاھدون Salafi Groups/ Al-QaedaRegistration required

1-2-3-4 Arabic 23 110 41

shahed4pal Salafi Groups/ Al-QaedaRegistration required

1-2-3-4 Arabic 25 132 85

islamic-union · اإلتحاداإلسالمي

Salafi Groups/ Al-QaedaRegistration required

1-2-3-4 Arabic 62 108 594

Some opposed users intentionally post attachments containing viruses to disrupt the operation of these groups.The number of postings increased in the month of July 2004.

Topic Map: Sub-topic identification

U.S. and Middle Eastern Intensity Scores

U.S. Middle Eastern

Forum Racism Violence Forum Racism Violence

Angelic Adolf 5.513 0.962 Azzamy 30.182 19.833Aryan Nation 9.921 5.683 Friends 2.076 6.238

CCNU 3.712 14.546 Islamic Union 2.657 9.198

Neo-Nazi 5.458 5.614 Kataeb 2.610 6.605

NSM 10.740 10.740 Kataeb Qassam 25.203 18.670

Smash Nazi 12.424 10.591 Taybah 14.989 15.348

White Knights 19.313 6.353 Osama Lover 14.369 14.584

World Knights 2.468 2.234 Wa Islamah 4.075 9.193

All Forums 10.988 6.902 All Forums 11.892 12.644

Case 2: TelCorp ExampleAhmedAbbasi,YiluZhou,Shasha Deng,Pengzhu Zhang

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•OneofthetenlargesttelecommunicationsanddataserviceprovidersintheUS

•Havea20+memberdedicatedsocialmediamonitoringteam

•Usesocialmediaanalysissystemthatprocesses43,000+messagesperday(1,800/hour)• Duringpeaktimes:5,000/hour;83/minute• About4,000discussionthreadupdatesperday

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• Fall2012– increasedmaxspeedsforpremiumInternetplancustomers• Announcedthroughvarioussocialmediachannels

•Monitoringteam24-hourassessmentof2,000newdiscussionthreads:overallsentimentpositive• However,callcenternoticeduptickincomplaints

• Next24-hours,monitoringteamcombeddata• Speedincreaseonlyappliedto20%ofcustomers• Poorlybroadcastedtoallcustomers• Createdinitialeuphoriafollowedbyconfusionandanger

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•Exactly54hoursaftertheinitialannouncement,thecompanymadeamendsby:• Introducingsimilarmaxspeedincreasesforcustomersonnon-

premiumplans• Providingpromotionaloffersonadditionalservicesandupgrades• Apologizingfortheconfusion

•Nevertheless,customerchurnratewas5x• Estimated$110millioninlostrevenueovernext12-months• Nottomentionlong-termlossesbasedoncustomerlifetimevalue

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LAP Goal

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ConversationDisentanglement

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• CoherenceAnalysis• Nearly50%ofmessagesindiscussionforumthreadsdon’trespondtopriororfirstposting• FacebookandTwitter:20%to30%• Systemlimitationsand/orlackofproperusageofsystemfeatures

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• SpeechActs

• TelCorpConversations:• Positiveexpressives early• Followedbyconversationsencompassingquestions,suggestions,assertionsof

indifference/negligence,negativeexpressives,anddeclarationsofhavingswitchedtootherproviders

• IncorporatesmanyLAPprinciples• Interplaybetweenconversations,interactions,andmessageacts• Importanceofconversationbeginnings• Contextualization,lexicalchaining,andthematization• Speechactinter-dependencies

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• PrimitiveMessageDetection• LeveragesLAPprincipleoflexical

chains(topic“breadcrumbs”)

§ Conversation Affiliation Classification• LeveragesLAPprincipleof

thematization• Examinesprimitive/secondary

messagesimilaritiesacrossthreadregions

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• PrimitiveMessageDetection

Wherewxt =tfxtidft ,tisoneofthek uniquetermsinX,

r isoneofthej uniquetermsinY,t andr arenouns,verbs,noun/verbphrases,ornamedentities

str isthesimilaritybetweentandr basedontheshortestpaththatconnectsthemintheis-a(hypernym/hypnoym)taxonomyinWordNet(Miller1995).

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• CoherenceAnalysisMethod

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Letsi,li,andci representthesystem,linguistic,andconversationstructurefeaturevectorsforagivenmessagepairX andY.

WedefineacombinatorialensembleofkernelsK= {K1…KQ}encompassingallcombinationsoflinearcompositekernelsinvolvings,l,andc (hereQ=7dueto23– 1totalcombinations).

Giventwoinstancerowsinthetrainingdatamatrix,theirsimilarityisdefinedbasedontheinnerproductbetweenallcombinationsoftheirthreevectorss1,l1,c1,ands2,l2,andc2.

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• SpeechActTwo-StageClassifier• LeveragesLAPprincipleaboutrelationbetweenspeechactsandmessageinteractions

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• SpeechActTreeKernelClassifierSimilarityFunction

KAC (xi,xj) isasimilaritymeasurebetweenSxi andSxj computedbycomparingalltreefragmentsinSxiandSxj,whereafragmentisdefinedasanysub-graphcontainingmorethanonenode(CollinsandDuffy2002).

KAC (xi,xj) issimplyequaltotwotimesthenumberofcommonfragmentsinSxi andSxj,dividedbythetotalnumberoffragmentsinSxi andSxj.

Formally,lethk(xi)denotethepresenceofthekthtreefragmentinSxi (wherehk(xi)=1ifthekthtreefragmentexistsinxi)suchthatSxi isnowrepresentedasabinaryvectorh(xi)=(h1(xi),…,hn(xi)):

• Four-monthA/Btest

• WorkedwithTelCorpITtoincorporateLTASwithexistingtopic-sentiment-basedsystem

• Split23-membermonitoringteamintotwogroups• A-team:12membersassignedtoexistingsystem• B-team:11membersassignedtonewsystemthatalsohadLTAS• Teamswerenotco-located,andonlyhadaccesstotheirrespectivesystem

• TelCorpreceived5.2millionsocialmediamessagesduringthe4-monthperiod

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OverviewofTelCorp’sSocialMediaMonitoringWorkflow

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Questions?