Altruism, Selfishness, and
Contribution
on the
th Social
S i lW
Web
b
John Riedl
GroupLens
p
Research
University of Minnesota
UNIVERSITY OF MINNESOTA
Bowling Alone
(Amazon
reviews)
UNIVERSITY OF MINNESOTA
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UNIVERSITY OF MINNESOTA
Messages
Web 2.0 is The Social Web
P
l Connecting
C
ti tto P
l
People
People
Technology Enabling Community
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Alexa Rankings
UNIVERSITY OF MINNESOTA
1. Google
Search
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Google PageRank
Value of a page is the value of the pages
that link to it
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 Smyth
AH’08
UNIVERSITY OF MINNESOTA
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The Long Tail
The Long Tail
In Blogspace
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Want to be a Millionaire?
Netflix $1M Challenge
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6
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Google Street View in UK
• My B&B in London
o
http://maps.google.co.uk/maps?f=q&source=s_q&hl=en&g
eocode=&q=high+street+kensington&sll=51.490643,d & hi h+ t t+k i t & ll 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,
-0.192387&panoid=8ACFOoEYapAmvgcuRoz_Q&cbp=12,79.63692756901483,,0,8.672391017173075
• Link to BBC Video
o
0:00 – 2:00
• Privacy Risks
o
o
Photos of people leaving sex shops
Photos of naked toddler playing in park
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Opportunity
How can we mine free activity?
Wh t are the
th risks
i k in
i these
th
d t ?
What
data?
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2. Yahoo!
Everything
UNIVERSITY OF MINNESOTA
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Flickr Popular Tags
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Picture of a Baby from Flickr
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Flickr Popular Tags
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Tag Selection
l i Algorithms
l
ih
“The Quest for Quality Tags”
S. Sen, F. Harper, A. LaPitz, J. Riedl
GROUP 2007
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Catcher in
the Rye
Huge number of tags
RQ: How can a tagging
system show users tags
they want to see?
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Users don’t agree
Most controversial tags (Bayesian expected entropy):
tag
entropy
#
#
comedy
d
0 987
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
17
quirky
0.977
25
20
magic
0.974
18
15
animation
0.974
26
20
Steven Spielberg
0.973
12
12
sci-fi
0.972
14
17
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Random baseline: 21%
Tag Prediction
Implicit features:
number of applications (39%)
number of users (51%)
number of searches for a tag (44%)
number of users who searched for a tag (48%)
length of tag (42%)
Moderation-based features:
global average rating for a tag (59%)
g rating
g for a tag
g ((62%))
user-normalized g
global average
tag reputation (57%)
Hybrid combinations: logistic regression, decision trees (67%)
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RealAge
UNIVERSITY OF MINNESOTA
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Opportunities
How can a system distinguish between
“good” tags and “bad” tags?
Can folksonomy be encouraged?
o
o
Showing users more tags leads to more
vocabulary reuse
How much convergence is valuable?
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3. Facebook
Social Networking for
College Students … and
everyone else
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The Predictive Power of Online
Chatter
• Gruhl, Guha,
Kumar, Novak,
Tomkins
• Yahoo
• ACM KDD 2005
• Volume of blog
postings predict
sales rank of books
• Queries can be
automatically
generated in many
cases.
• Can sometimes
predict spikes in
sales rank.
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Anti-aliasing on the Web
Jasmine Novak,
Prabhakar
R h
Raghavan,
A
Andrew
d
Tomkins.
WWW 2004
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Story: Finding Medical Records
(Sweeney 2002)
Former Governer of Massachussetts!
Medical Data
Ethnicity
Zip
Visit Date
Diagnosis Birthdate
Sex
Procedure
Medication
Total Charge
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V t List
Li t
Voter
Name
Address
Date registered
Party
P t affiliation
ffili ti
Date last voted
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Cat Torturer Video
• YouTube Link
• 1:10
1 10 – 2:15
2 15
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17
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Discussion
Social Implications
O
t iti
Opportunities
Threats
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4. YouTube
Video by Amateurs?
Copyright issues
• Music videos
• CBS agreement
UNIVERSITY OF MINNESOTA
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Why did Google Buy YouTube?
$1,650 / 65 = $25 million / employee
$1 650 / 100 million
illi views
i
d =
$1,650
per day
$16
$16 / 365 = $.04½ / view / year
… but Google already had videos!
The technology?
The community!
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Second Life
Virtual World
P
l “live”,
“li ” buy,
b
d sell
ll th
People
and
there
$60M (US $) worth of “manufactured
goods” sold this year
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Making a Guitar in Second Life
0:45 – 1:45
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World of Warcraft
A different virtual world
M
f
b t
More
focus
on combat
6 million subscribers
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Fayejin Funeral
On Tuesday of February 28th Illidan lost
not only a good mage
mage, but a good
person. For those who knew her,
Fayejin was one of the nicest people
you could ever meet. On Tuesday she
suffered from a stroke and passed away
later
that
l
h night.
i h
5:30 March 4th, Frostfire Hot Springs
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World of Warcraft Video
UNIVERSITY OF MINNESOTA
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“I hope azshira’s dad dies of a heart
attack then at the funeral some guy
attack,
runs in naked and pushes the coffin
over and runs around slapping people
screaming LOL OWNED, then releases
a video of it”
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Economist in EVE
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23
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MMOG Active Subscribers
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25
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Offshore to a Virtual World?
• Nick Yee @ PARC
• Some
S
radiology
di l
offshored
ff h d to
t IIndia
di
• Skill in a game: RADAR expert?
o
o
Learn to detect patterns
Rewards for correctness
• Wisdom of Crowds to combine results
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Jim Gray Mechanical Turk
Search
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Suicide streamed live on Justin.tv
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Chocolate Rain
by Tay Zonday
Adam Bahner, a Ph.D. student in
American Studies at the University of
Minnesota
Number 2 hottest viral video in history
o
o
Hottest viral video of Summer 2007
Over 26 million views
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Videos Life Fast, Die Young
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Huberman Dynamics of Viral
Marketing
The 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,
Éva Tardos, KDD’03
Independent Cascade Model
o
o
I f
ti diffuses
diff
ti
Information
over time
Each neighbor who converts has a one-time
chance to convert others
Linear Threshold Model
o
o
Each node considers the p
preferences of all
neighbors
If total weight passes threshold, a node
converts
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Video suggestion and discovery for YouTube: Taking random
walks through the view graph
Shumeet Baluja, et al., Google, WWW 2008
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Opportunities
Crowd-sourcing
G i as W
k?
Gaming
Work?
How do preferences propagate
naturally?
What predicts fads?
How do recommenders influence
propagation?
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5. MySpace
Social Network
UNIVERSITY OF MINNESOTA
MySpace
UNIVERSITY OF MINNESOTA
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Heather Ann Tucci
“I just want to let everyone know
August 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
because I was the driver but think about
how
many off you did what
did.”
h
h I did
”
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Twitter
Story about VC lunch
H d
i
i t
Hudson
river
pictures
NYT Tweets during superbowl
NBA Player who tweeted during halftime of a game
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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
in 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 lload
dd
) B
d off this
hi
one.
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Discussion
Social Implications
O
t iti
Opportunities
Threats
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6. Windows Live
7. MSN
ISP and Content Provider
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8. Wikipedia
Next slide, please!
UNIVERSITY OF MINNESOTA
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Wikipedia on Wikipedia
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Wikiality on MySpace
1:20 – 2:15: edit wikipedia to make truth
“What if the number of elephants in
Africa were increasing?”
UNIVERSITY OF MINNESOTA
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Creating, Destroying,
Reid Priedhorsky
and Restoring Value in
Jilin Chen
Wikipedia
p
Shyong (Tony) K.
Group 2007
Lam
Katherine Panciera
Loren Terveen
John
h Riedl
dl
UNIVERSITY OF MINNESOTA
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Who contributes
Wikipedia’s value?
3.8 million least
frequent editors
User:Maveric149
0.5% of valueWales 14% of value
Swartz
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PWV contributions of elite editors
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Challenges
How can vandalism be detected?
H
ffi i t is
i Wiki
di ?
How
efficient
Wikipedia?
How much conflict is valuable?
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9. Ebay
Online Auctions
Customers Selling to
Customers
UNIVERSITY OF MINNESOTA
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•EBay
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Amazon (# 13)
Most Important Resource is Customers
Customers “Selling to” Customers
UNIVERSITY OF MINNESOTA
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Amazon
Robertson
shilled
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Google Trends Front Page
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4Chan vs. eBaumsWorld
4Chan
o
o
Google Trends Hack
Chocolate Rain
eBaumsWorld
o
o
Many other hacks
py g
g with 4chan
“copyright”
fight
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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.
world ”
- Encyclopedia Dramatica
UNIVERSITY OF MINNESOTA
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The Social Cost of Cheap Pseudonyms
Friedman and Resnick, Journal of Economics
and Management Strategy,
Strategy 2001
The Information Cost of ManipulationResistance in Recommender Systems
Resnick and Sami. ACM RecSys 08.
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Increasing Contributions
UNIVERSITY OF MINNESOTA
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What Theory Tells Us…
Collective Effort Model
o People will contribute more if:
ƒ They believe their effort is important to the
group
ƒ They like the group
Smaller is Better
o
o
Slovic, Fischhoff, & Lichtenstein, 1980
People feel greater concern when the reference
group they’re part of grows smaller.
Specificity Matters
o
o
Small & Loewenstein, 2003
Specific identity of those helped is important in
drawing people’s support.
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CommunityLab Research
Social science to increase contributions
o
o
Accessible to designers
Algorithms, interfaces, toolkits
GroupLens @ Minnesota
o
o
Recommender algorithms and interfaces
John Riedl, Joe Konstan, Loren Terveen
Bob Kraut and Sara Kiesler @ CMU
o
Social psychology of computer use
Paul Resnick and Yan Chen @ Michigan
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VOICE 2 Screen shot
Numerical values
are represented
by smilies
Who the contribution
helps
Value of each
contribution
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Results
Behavioral data
Self-report
Self 3.87
Self 7.2%
All MovieLens 10.2%
All MovieLens 3.13
Similar Group 2.97
Similar Group 15.8%
1: Strongly Disagree
2: Disagree
3: Neutral
4: Agree
5: Strongly Agree
Dissimilar Group
2.94
Dissimilar
Group 5.9%
Control 7.4%
Control 2.68
1
2
3
4
0%
5
Want Smilies on the regular interface?
98
5%
10%
15%
20%
Probability of rating a movie
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Opportunities
How can contributors be motivated?
H
i l attacks
tt k b
iti t d?
How
can social
be mitigated?
o
Mail list “unsubscribe”
How does social psychology interact
with defense algorithms?
o
Can the griefers be encouraged to give up?
Can freedoms be preserved?
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10. Craigslist.org
Renting Apartments in NYC
$10/posting: $2.5M/year
Could generate $500M/year with
ads
“users haven’t asked for banner
ads”
ads
UNIVERSITY OF MINNESOTA
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http://www.cagle.com/news/DyingNewspap
ers/main.asp
UNIVERSITY OF MINNESOTA
UNIVERSITY OF MINNESOTA
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Reuters 2nd Life Bureau
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Messages
Web 2.0 is The Social Web
P
l Connecting
C
ti tto P
l
People
People
Technology Enabling Community
105
Carlson School March 2009
Altruism, Selfishness, and
Contribution
on the
th Social
S i lW
Web
b
John Riedl
GroupLens
p
Research
University of Minnesota
UNIVERSITY OF MINNESOTA
53
Discussion Topics
What will happen with virtual
economies?
Why did Google buy YouTube?
Broadcast -> Narrowcast -> Virtual Life
Copyright in the Digital Age
Governing Online Communities
107
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108
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The Social Cost of Cheap
Pseudonyms
The Value of Reputation on
eBay: A Controlled Experiment
UNIVERSITY OF MINNESOTA
Web site visualization
•Web
Web link
structure in
hyperbolic
space
•from
Tamara
Munzner
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Videos for this Presentation, for
Kevin
After (7) YouTube
Making a Guitar in Second Life
0:45 – 1:45
Suzanne Vega Concert in Second Life
1:00 – 1:40
World of Warcraft Video
0:00 – 2:05 (entire video)
p
After ((9)) Wikipedia
Wikiality on YouTube
1:20 – 2:15: edit wikipedia to make truth
111
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Bit Bucket
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