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Alt i S lfi h d Altruism, Selfishness, and Contribution Contribution on the Social Web John Riedl GroupLens Research Ui it f Mi t University of Minnesota UNIVERSITY OF MINNESOTA
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Alt i S lfi h dAltruism, Selfishness, and ContributionContribution

on the Social WebJohn Riedl

GroupLens ResearchU i it f Mi tUniversity of Minnesota

UNIVERSITY OF MINNESOTA

Bowling Alone g(Amazon

i )reviews)

UNIVERSITY OF MINNESOTA

UNIVERSITY OF MINNESOTA

Messagesg

Web 2.0 is The Social WebPeople Connecting to PeopleTechnology Enabling CommunityTechnology Enabling Community

Carlson School March 20094

Alexa Rankingsg

UNIVERSITY OF MINNESOTA

1. Google

Search

UNIVERSITY OF MINNESOTA

Carlson School March 20097

Google PageRankg g

Value of a page is the value of the pages p g p gthat link to itRecursive!Recursive!Fight for Attention: The Shoe Store

The Rich get Richer

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Web Structure

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(Web Search)shared( )

Maurice Coyle and Barry SmythAH’08

UNIVERSITY OF MINNESOTA

The Long Tailg

The Long TailIn Blogspaceg p

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Want to be a Millionaire?

Netflix $1M Challengeg

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Carlson School March 200913

Google Street View in UKg• My B&B in London

h // l k/ ?f & &hl &o http://maps.google.co.uk/maps?f=q&source=s_q&hl=en&geocode=&q=high+street+kensington&sll=51.490643,-0.158637&sspn=0.010515,0.016243&ie=UTF8&ll=51.505203,-0.193301&spn=0,359.991878&z=17&layer=c&cbll=51.505309,0.193301&spn 0,359.991878&z 17&layer c&cbll 51.505309,-0.192387&panoid=8ACFOo-EYapAmvgcuRoz_Q&cbp=12,79.63692756901483,,0,-8.672391017173075

• Link to BBC Videoo 0:00 – 2:00

• Privacy RisksPrivacy Riskso Photos of people leaving sex shopso Photos of naked toddler playing in park

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Opportunitypp y

How can we mine free activity?f yWhat are the risks in these data?

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2. Yahoo!

Everything

UNIVERSITY OF MINNESOTA

Flickr Popular Tags

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Picture of a Baby from Flickry

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Flickr Popular Tags

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Tag Selection Algorithms

“The Quest for Quality Tags”S. Sen, F. Harper, A. LaPitz, J. RiedlGROUP 2007

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Catcher in the Rye

Huge number of tagsRQ: How can a tagging system show users tags system show users tags

they want to see?

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Users don’t agreeMost controversial tags (Bayesian expected entropy):

tag entropy # #tag entropy # #comedy 0.987 28 30

classic 0.986 25 24

stylized 0.983 20 21

nudity (full frontal) 0.980 18 20

romance 0 980 18 17romance 0.980 18 17

quirky 0.977 25 20

magic 0.974 18 15

animation 0.974 26 20

Steven Spielberg 0.973 12 12

i fi 0 972 14 17

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sci-fi 0.972 14 17

Tag PredictionR d b li 21%

gRandom baseline: 21%

Implicit features:number of applications (39%)number of applications (39%)number of users (51%)number of searches for a tag (44%)number of users who searched for a tag (48%)number of users who searched for a tag (48%)length of tag (42%)

Moderation-based features:global average rating for a tag (59%)user-normalized global average rating for a tag (62%)tag reputation (57%)tag reputation (57%)

Hybrid combinations: logistic regression, decision trees (67%)

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RealAgeg

UNIVERSITY OF MINNESOTA

Opportunities

How can a system distinguish between How can a system distinguish between “good” tags and “bad” tags?C f lk b d? Can folksonomy be encouraged? o Showing users more tags leads to more

b l vocabulary reuse o How much convergence is valuable?

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3. Facebook

Social Networking for College Students … and everyone else

UNIVERSITY OF MINNESOTA

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Carlson School March 200929

Carlson School March 200930

The Predictive Power of Online ChatterChatter

• Gruhl, Guha, • Volume of blog Kumar, Novak, Tomkins

gpostings predict sales rank of books

• Yahoo• ACM KDD 2005

• Queries can be automatically

t d i generated in many cases.

• Can sometimes • Can sometimes predict spikes in sales rank.

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sales rank.

Anti-aliasing on the WebJasmine Novak,

Prabhakar Prabhakar Raghavan, Andrew Tomkins Tomkins.

WWW 2004

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Story: Finding Medical Records (Sweeney 2002)(Sweeney 2002)

Former Governer of Massachussetts!Medical DataEthnicity

Voter ListName

ZipBi thd t

EthnicityVisit DateDi i

NameAddressZip

Bi thd tBirthdateSex

DiagnosisProcedure

Date registeredParty affiliation

BirthdateSex

MedicationTotal Charge

yDate last voted

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Total Charge

Cat Torturer Video

• YouTube Link• 1:10 – 2:15

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Carlson School March 200935

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Discussion

Social ImplicationspOpportunitiesThreatsThreats

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4. YouTube

Video by Amateurs?C i h iCopyright issues• Music videos• CBS agreement• CBS agreement

UNIVERSITY OF MINNESOTA

Why did Google Buy YouTube?y g y

$1,650 / 65 = $25 million / employee, / / p y$1,650 / 100 million views per day = $16$16$16 / 365 = $.04½ / view / year

b t G l l d h d id !… but Google already had videos!

The technology?The community!

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The community!

Second Life

Virtual WorldPeople “live”, buy, and sell there$60M (US $) worth of “manufactured $60M (US $) worth of manufactured goods” sold this year

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Making a Guitar in Second Life

0:45 – 1:45

UNIVERSITY OF MINNESOTA

World of Warcraft

A different virtual worldMore focus on combat6 million subscribers6 million subscribers

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Fayejin Funeraly j

On Tuesday of February 28th Illidan lost y ynot only a good mage, but a good person. For those who knew her, p ,Fayejin was one of the nicest people you could ever meet. On Tuesday she y ysuffered from a stroke and passed away later that night.g5:30 March 4th, Frostfire Hot Springs

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World of Warcraft Video

UNIVERSITY OF MINNESOTA

“I hope azshira’s dad dies of a heart pattack, then at the funeral some guy runs in naked and pushes the coffin pover and runs around slapping people screaming LOL OWNED, then releases g ,a video of it”

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Economist in EVE

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Carlson School March 200947

MMOG Active Subscribers

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Carlson School March 200949

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Carlson School March 200951

Carlson School March 200952

Offshore to a Virtual World?

• Nick Yee @ PARC• Some radiology offshored to India• Skill in a game: RADAR expert?• Skill in a game: RADAR expert?

o Learn to detect patternsR d f to Rewards for correctness

• Wisdom of Crowds to combine results

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Jim Gray Mechanical Turk S hSearch

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Suicide streamed live on Justin.tv

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Chocolate Rainb T Z dby Tay Zonday

Adam Bahner a Ph D student in Adam Bahner, a Ph.D. student in American Studies at the University of MinnesotaMinnesotaNumber 2 hottest viral video in historyo Hottest viral video of Summer 2007o Over 26 million views

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Videos Life Fast, Die Young, g

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Carlson School March 200958

Huberman Dynamics of Viral M k tiMarketingThe Dynamics of Viral Marketing,

ACM TWeb 2007, Leskovec et al., HP

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Maximizing the Spread of Influence through a Social Network, David Kempe, Jon Kleinberg,

ÉÉva Tardos, KDD’03

Independent Cascade Modelpo Information diffuses over timeo Each neighbor who converts has a one-timeo Each neighbor who converts has a one time

chance to convert othersLinear Threshold ModelLinear Threshold Modelo Each node considers the preferences of all

neighborsneighborso If total weight passes threshold, a node

converts

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converts

Video suggestion and discovery for YouTube: Taking random gg y gwalks through the view graph

Shumeet Baluja, et al., Google, WWW 2008

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Opportunitiespp

Crowd-sourcinggGaming as Work?How do preferences propagate How do preferences propagate naturally?Wh t di t f d ?What predicts fads?How do recommenders influence propagation?

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5. MySpace

Social Network

UNIVERSITY OF MINNESOTA

MySpace

UNIVERSITY OF MINNESOTA

Heather Ann Tucci

“I just want to let everyone know j yAugust 19 2006 Joe Renner and Joe Shafer died and me and Samatha were hurt. … Both of them knew what they were getting in to. Yes it’s my fault g g ybecause I was the driver but think about how many of you did what I did.”y y

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Twitter

Story about VC lunchyHudson river picturesNYT Tweets during superbowlNYT Tweets during superbowlNBA Player who tweeted during half-ti f time of a game

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Carlson School March 200967

So I once went on a movie date with a guy who thought it was sort of weird that I posted to Twitter about the movie pin mid-date. In retrospect, it probably was weird, and a bit rude, and I , ,wouldn't do it again (and no, there was no second date). But get a load of this ) gone.

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Discussion

Social ImplicationspOpportunitiesThreatsThreats

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6. Windows Live7. MSN

ISP and Content Provider

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8. Wikipedia

Next slide, please!

UNIVERSITY OF MINNESOTA

Wikipedia on Wikipediap p

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Wikiality on MySpace

1:20 – 2:15: edit wikipedia to make truth“What if the number of elephants in pAfrica were increasing?”

UNIVERSITY OF MINNESOTA

Creating DestroyingCreating, Destroying, and Restoring Value in

Wiki diReid PriedhorskyJilin Chen Wikipedia

Group 2007Jilin ChenShyong (Tony) K. Lam pLamKatherine PancieraLoren TerveenJohn RiedlJ

UNIVERSITY OF MINNESOTA

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Who contributes Wikipedia’s value?Wikipedia’s value?

User:Maveric149 3.8 million least frequent editorsfrequent editors

0.5% of value 14% of valueWales

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Swartz

PWV contributions of elite editors

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Challengesg

How can vandalism be detected?How efficient is Wikipedia?How much conflict is valuable?How much conflict is valuable?

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9. Ebay

Online AuctionsCustomers Selling to Customers

UNIVERSITY OF MINNESOTA

•EBay

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Amazon (# 13)

Most Important Resource is Customers Customers “Selling to” CustomersCusto e s Se g to Custo e s

UNIVERSITY OF MINNESOTA

Amazon R b tRobertson

shilledshilled

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Google Trends Front Pageg g

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4Chan vs. eBaumsWorld

4Chano Google Trends Hacko Chocolate Raino Chocolate Rain

eBaumsWorldMany other hackso Many other hacks

o “copyright” fight with 4chan

Carlson School March 200990

UNIVERSITY OF MINNESOTA

The Internet is Serious Business

“A phrase used to remind those who voluntarily leave the house that being mocked on the Internet is, in fact, the end of the world.”- Encyclopedia Dramatica

UNIVERSITY OF MINNESOTA

The Social Cost of Cheap PseudonymsFriedman and Resnick, Journal of EconomicsFriedman and Resnick, Journal of Economics and Management Strategy, 2001

Th I f i C f M i l iThe Information Cost of Manipulation-Resistance in Recommender Systems R i k d S i ACM R S 08Resnick and Sami. ACM RecSys 08.

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Increasing Contributionsg

UNIVERSITY OF MINNESOTA

What Theory Tells Us…Collective Effort Modelo People will contribute more if:

h b l h ff hThey believe their effort is important to the groupThey like the group

Smaller is Bettero Slovic, Fischhoff, & Lichtenstein, 1980o People feel greater concern when the reference o People feel greater concern when the reference

group they’re part of grows smaller.Specificity Matters

S ll & L t i 2003o Small & Loewenstein, 2003o Specific identity of those helped is important in

drawing people’s support.

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CommunityLab ResearchySocial science to increase contributionso Accessible to designerso Algorithms, interfaces, toolkits

GroupLens @ Minnesotao Recommender algorithms and interfaceso Recommender algorithms and interfaceso John Riedl, Joe Konstan, Loren Terveen

Bob Kraut and Sara Kiesler @ CMUBob Kraut and Sara Kiesler @ CMUo Social psychology of computer use

P l R i k d Y Ch @ Mi hiCarlson School March 200996

Paul Resnick and Yan Chen @ Michigan

VOICE 2 Screen shotNumerical values are represented

by smiliesby smilies

Who the contribution h lhelps

Value of each contribution

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ResultsResultsSelf-report Behavioral data

Self 3.87 Self 7.2%

1: Strongly Disagree

All MovieLens 3.13

Similar Group 2.97

All MovieLens 10.2%

Similar Group 15.8%

2: Disagree3: Neutral4: Agree5: Strongly Agree

Dissimilar Group

2.94

Control 2.68

Dissimilar

Group 5.9%

Control 7.4%

Want Smilies on the regular interface?

1 2 3 4 5 0% 5% 10% 15% 20%

Probability of rating a movie

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Opportunitiespp

How can contributors be motivated?How can social attacks be mitigated?o Mail list “unsubscribe”o Mail list unsubscribe

How does social psychology interact with defense algorithms?with defense algorithms?o Can the griefers be encouraged to give up?

f d b dCan freedoms be preserved?

Carlson School March 200999

10. Craigslist.org

Renting Apartments in NYC$10/posting: $2 5M/year$10/posting: $2.5M/yearCould generate $500M/year with ads“users haven’t asked for banner ads”

UNIVERSITY OF MINNESOTA

http://www.cagle.com/news/DyingNewspapers/main.asp

UNIVERSITY OF MINNESOTA

UNIVERSITY OF MINNESOTA

UNIVERSITY OF MINNESOTA

Reuters 2nd Life Bureau

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Messagesg

Web 2.0 is The Social WebPeople Connecting to PeopleTechnology Enabling CommunityTechnology Enabling Community

Carlson School March 2009105

Alt i S lfi h dAltruism, Selfishness, and ContributionContribution

on the Social WebJohn Riedl

GroupLens ResearchU i it f Mi tUniversity of Minnesota

UNIVERSITY OF MINNESOTA

Discussion Topicsp

What will happen with virtual ppeconomies?Why did Google buy YouTube?Why did Google buy YouTube?Broadcast -> Narrowcast -> Virtual LifeC i ht i th Di it l ACopyright in the Digital AgeGoverning Online Communities

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The Social Cost of Cheap PseudonymsPseudonyms

The Value of Reputation on eBay: A Controlled ExperimenteBay: A Controlled Experiment

UNIVERSITY OF MINNESOTA

W b it i li tiWeb site visualization

•Web link structure in hyperbolic space

•from T Tamara Munzner

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Videos for this Presentation, for KevinKevin

After (7) YouTubeMaking a Guitar in Second Life0:45 – 1:45Suzanne Vega Concert in Second LifeSuzanne Vega Concert in Second Life1:00 – 1:40World of Warcraft Video

( d )0:00 – 2:05 (entire video)After (9) WikipediaWikiality on YouTubeWikiality on YouTube1:20 – 2:15: edit wikipedia to make truth

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Bit Bucket

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