an empirical study of the spread of news on digg and twitter … · • digg’s user interface...

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Information Contagion: An Empirical Study of the Spread of News on Digg and Twitter Social Networks Kris%na Lerman Rumi Ghosh USC Informa,on Sciences Ins,tute

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Page 1: An Empirical Study of the Spread of News on Digg and Twitter … · • Digg’s user interface gives high visibility to promoted stories • Promoon slows informaon spread • Digg’s

Information Contagion: An Empirical Study of the Spread of News

on Digg and Twitter Social Networks

Kris%naLermanRumiGhosh

USCInforma,onSciencesIns,tute

Page 2: An Empirical Study of the Spread of News on Digg and Twitter … · • Digg’s user interface gives high visibility to promoted stories • Promoon slows informaon spread • Digg’s

USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 2

OnlineSocialNetworks

Onlinesocialnetworkshavebecomeimportantchannelsforthespreadof,melyandrelevantinforma,on

poweredbyTouchGraph

Page 3: An Empirical Study of the Spread of News on Digg and Twitter … · • Digg’s user interface gives high visibility to promoted stories • Promoon slows informaon spread • Digg’s

USC Information Sciences Institute

Informa%onflowonnetworks

hGp://www.flickr.com/photos/27318782@N03/4639307923

3

Network2Network1

http://www.flickr.com/photos/27318782@N03/4639307471/

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 4

DynamicsofSocialInforma%on

Page 5: An Empirical Study of the Spread of News on Digg and Twitter … · • Digg’s user interface gives high visibility to promoted stories • Promoon slows informaon spread • Digg’s

USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 5

Socialnews:Digg

Userssubmitandvotefor(digg)newsstories

Usersjoinnetworkstosee•  Storiesfriendssubmit

•  Storiesfriendsvotefor

Diggfeaturesstorieswithmostvotesonitsfrontpage

Page 6: An Empirical Study of the Spread of News on Digg and Twitter … · • Digg’s user interface gives high visibility to promoted stories • Promoon slows informaon spread • Digg’s

USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 6

Socialnews:TwiDer+TweetmemeUserstweetandretweet*URLstonewsstories

*‘Retweet’=tweetsomeoneelse’spost

“RT@xfailedbombplothGp://bit.ly/xmas09”

Usersjoinnetworkstosee•  Tweetsbyuserstheyfollow•  Retweetsbyuserstheyfollow

TweetmemeaggregatesalltweetsandfeaturesmostretweetedURLsonitsfrontpage

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 7

Socialnews:Datasets

Digg• Stories

•  3,553stories,promotedinJune,2009

•  TimesubmiGed,promoted•  Votesforeachstory

•  Timeofthevote•  Nameofvoter

• Ac,veusers•  139,409whovotedforatleast

onestory•  71,834ofthemfollowingat

leastoneuser•  258,220links•  fannetwork

TwiGer• Stories

•  398mostretweetedstories6/11/09—7/3/09

•  extractedfromTweetmeme•  Retweetsofeachstory

•  <1000mostrecentretweets•  Timeofretweet&username

• Ac,veusers•  137,582whoretweetedatleast

onestory•  Following/followerrela,ons

throughTwiGerAPI•  6,200,051links•  followernetwork

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 8

Ques%ons

Page 9: An Empirical Study of the Spread of News on Digg and Twitter … · • Digg’s user interface gives high visibility to promoted stories • Promoon slows informaon spread • Digg’s

USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 9

Basicterms

SubmiGer•  userwhosubmiGedlinktoastory•  userwhofirsttweetedlinktoastory

Vote•  digg•  retweet

FanofuserA•  userwatchingA’sac,vityonDigg•  userfollowingAonTwiGer

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 10

Userac%vity:distribu%onoffans

TwiGerDigg

• TypicalnumberoffollowersonTwiGer~10,butcanbemillions• NotypicalnumberoffansonDigg–“longtail”

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 11

Userac%vity:distribu%onofvo%ng

TwiGer

• “Longtail”distribu,onofuserac,vity• Differenceinsloperelatedtoeffortofac,vity[cfWilkinson2008]

Digg

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 12

Dynamicsofstories

Digg TwiGer

1:U.S.GovernmentAsksTwiGertoStayUpfor#IranElec,on2:WesternCorpora,onsHelpedCensorIranianInternet3:Iranianclericsdefyayatollah,joinprotests

1:USgovaskstwiGertostayup2:IranHasBuiltaCensorshipMonsterwithhelpofwesttech3:ClericsjoinIran’san,‐governmentprotests‐CNN.com

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 13

Dynamicsofstories

Digg TwiGer

• Twodis,nctphasesforDiggstories:upcomingandpromoted• Numberofvotesonbothsitessaturatesaveroneday• Saturatedvaluereflectsstorypopularity

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 14

Popularityofstories

Digg TwiGer

lognormalfit lognormalfit

• AggregateoverallstoriestofactoroutinfluenceofsubmiGerandstoryquality• “Inequalityofpopularity”–somestoriesmuchmorepopularthanothers

cfsocialinfluencestudyof[Salganik,Dodds&WaGs,2006]

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 15

Informa%onflowonnetworks

Informa,onspreadsonanetworkasfans(followers)votefor(retweet)storiestheirfriendssubmitorvotefor.

…fanvotes–i.e.,votesfromfans

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 16

Dynamicsofinforma%onspreadonnetworks

Digg TwiGer

fan

vote

s

follo

wer

retw

eets

• Evolu,onoffanvotesqualita,velysimilartothatofallvotes

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 17

Howfardoesinforma%onspreadonnetworks?

Digg TwiGer

normalfitnormalfit

Page 18: An Empirical Study of the Spread of News on Digg and Twitter … · • Digg’s user interface gives high visibility to promoted stories • Promoon slows informaon spread • Digg’s

USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 18

Howfardoesinforma%onspreadamongsubmiDer’sfans?

numberofretweetsfromsubmiDer’sfollowers

Digg TwiGer

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 19

Howfastdoesinforma%onspreadonnetworks?

• Twodis,nctphasesonDigg:storiesspreadfasterthroughthenetworkbeforepromo,onthanaverwards• TwiGerstoriesspreadatauniformrate,butwithgreatervariability

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 20

Howfastdoesinforma%onspreadonnetworks?

Probabilitynextvoteisfromafan

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 21

Networkstructure

Networksamplesize•  Digg:279,725users•  TwiGer:6,200,051users

Networkdensity•  Frac,onofreciprocallinks(i.e.,mutualfans)

•  Digg:fm=3.20x10‐6•  TwiGer:fm=2.07x10‐7

•  Modifiedclusteringcoefficient(frac,onofcycles,e.g.,ABCA)

•  Digg:fc=7.60x10‐12•  TwiGer:fc=1.92x10‐14

Diggnetworkisdenser,moreinter‐connectedthanTwiGer’s

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 22

Summaryofresults

Networkstructureandinforma,onflow•  Digg’snetworkisdenserthanTwiGer’s

•  Newsspreadsfasterini,allythroughDigg’snetworkthanTwiGer’s•  But,itdoesnotspreadasfarasonTwiGer•  FanswhovoteforastoryonDiggarealsosubmiGer’sfans

•  TwiGer’snetworkissparse•  FansunconnectedtosubmiGerhelpspreadthestory

Userinterfaceandinforma,onflow•  Beforepromo,on,Diggstoriesspreadmainlythroughthenetwork

•  SimilartostoryspreadonTwiGer

•  Averpromo,on,storiesspreadmainlyoutsidethenetwork•  Promo,onincreasesstoryvisibilityoutsidethenetwork

•  NoequivalentmechanismonTwiGer

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 23

Relatedwork

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USC Information Sciences Institute

Kris,naLerman(CC)‐ICWSM2010 24

Conclusion

Compara,veempiricalanalysisofonlinesocialnetworksandsocialnewsonDiggandTwiGer

•  Similari,es•  Networksareusedonbothsitestospreadnews•  Informa,onflowonDiggbeforepromo,onissimilartoinforma,onflow

onTwiGer

•  Differencesindynamicscanbeexplainedbyuserinterfaceandnetworkdensity•  Digg’suserinterfacegiveshighvisibilitytopromotedstories

•  Promo,onslowsinforma,onspread

•  Digg’snetworkisdenserthanTwiGer’s•  Affectshowfastandhowfarnewsspreads

•  Dynamicsofinforma,onflowasagaugeofinforma,onquality•  SocialdynamicsofDigg[Hogg&Lerman,poster][Lerman&Hogg,WWW2010]