The Facebook
Application Market
Tim O’Reilly
O’Reilly Media, Inc.
www.oreilly.com
Graphing Social Networks
October 9, 2007

We’re best known as a book publisher
2

What We Really Do At O'Reilly
Change the world by spreading the
knowledge of innovators
3

How we do it
• Find interesting technologies and people
innovating from the edge
• Amplify their effectiveness by spreading
the information needed for others to
follow them.
• Books
4

How we do it
• Find interesting technologies and people
innovating from the edge
• Amplify their effectiveness by spreading
the information needed for others to
follow them.
• Books, Conferences
5

How we do it
• Find interesting technologies and people
innovating from the edge
• Amplify their effectiveness by spreading
the information needed for others to
follow them.
• Books, Conferences, Online
6

Watch the Alpha Geeks
• New technologies first exploited by hackers, then
entrepreneurs, then platform players
• Three examples
– Wireless community networks
predict universal Wi-Fi
– Screen scraping predicts
web services and the internet
as platform
– “The pedal powered internet”
predicts new focus on energy
Rob Flickenger and his potato chip can antenna
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Facebook is the new frontier
What is it telling us?
8

Data from O’Reilly Research
• http://radar.oreilly.com/
research/reports/
facebook.html
• Prepared by Tim O’Reilly,
Roger Magoulas, Ben
Lorica, Jimmy Guterman,
with contributions from
Dave McClure, Niall
Kennedy, Max Levchin,
and Ali Partovi
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Methodology
• Spidered Facebook stats weekly from 7/29
to 9/2
• On 9/4, Facebook started reporting
engagement. Switched spidering to daily.
• After 9/4, total installs per app is inferred
from percentage
• Total installs used for historical and rate of
change data, active user data for application
ranking
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11
Millions
10
15
20
25
0
5
9/4
/07
9/5
/07
9/6
/07
9/7
/07
9/8
/07
(on average)
9/9
Facebook Daily Active Users
/07
9/1
0/0
7
9/1
1/0
7
9/1
2/0
7
9/1
3/0
7
9/1
4/0
7
9/1
5/0
7
9/1
6/0
7
9/1
7/0
7
9/1
8/0
7
9/1
9/0
7
Facebook growing by 1.14% per day
9/2
0/0
7
9/2
1/0
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Applications Growing Even Faster -
1.9% per day
4,500
Facebook Application Count (by week)
3,000
1,500
0
7/29/07 8/5/07 8/12/07 8/19/07 8/26/07 9/2/07 9/9/07 9/16/07
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87% of Usage Goes to 2% of Apps
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The Top 50 Developers by Usage
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- no header version
Here’s the graph against all 5000+
apps
3,500,000
3,000,000
2,500,000
2,000,000
1,500,000
1,000,000
500,000
0
0 1,000 2,000 3,000 4,000 5,000 6,000
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Safari Views vs. Bookscan Unit Sales
Additional demand from the
long tail effect

A Power Law Distribution
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R-squared is a measure of how well a line fits the data that ranges from 0 to 1. The higher the R-squared value, the better the line fits the data. F
a power law distribution, an R-squared of .85 or better is expected. The Facebook app distribution with R-squared = .658 doesn’t show a Power
Law distribution. The distribution isn’t linear.
Facebook Application Usage
log (active users) 12
Active Users / True Rank (loglog)
w/ linear regression
10
8
y = -3.2924x +
11.33
6 R2 = 0.658
4
2
0
0 1 2 3 4
log (true rank)
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Many Applications Competing for the
Average Application Adoption
Same User
1% Application Adoption and Application Counts by Category (9/21/2007)
Dating
Messaging
Chat
Video
Just for Fun
Alerts
Gaming
Photo
Utility
0%
0 400 800 1200 1600 2000
Application Count by Category
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Categories with the most active
users per application (average)
Sports
Gaming
Chat
Fashion
Just for Fun
Photo
Travel
Dating
Food and Drink
Messaging
Music
Mobile
Events
Video
Utility
File Sharing
Alerts
Education
Business
Politics
Money
Classified Avg % Active Users by Category
All
0% 5% 10% 15%
20

Most Active Categories, by Number
of Applications > 100,000 users
Just for Fun
Messaging
Gaming
Video
Dating
Chat
Alerts
Photo
Utility
Travel
Education
Politics
Music
Mobile
Food and Drink
Fashion
Events
Sports
Money
File Sharing
Classified
Applications by Category > 100K Active Users
Business
All
0 10 20 30 40 50
21

Most Active Categories, Percentage
of Applications > 100,000 users
Messaging
Dating
Gaming
Video
Just for Fun
Chat
Alerts
Travel
Photo
Mobile
Fashion
Food and Drink
Education
Politics
Events
Music
Utility
Sports
Money
File Sharing
Classified
Business
Proportion of Application w/ >100K Active Users
All
0% 2% 4% 6%
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Most Active Categories, by Number
of Applications > 25,000 users
Just for Fun
Gaming
Messaging
Dating
Photo
Chat
Alerts
Video
Utility
Food and Drink
Events
Travel
Mobile
Education
Music
File Sharing
Fashion
Politics
Money
Business
Sports
Applications by Category > 25K Active Users
Classified
All
0 10 20 30 40 50 60 70 80 90 100 110
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Most Active Categories, Percentage
of Applications > 25,000 users
Messaging
Dating
Gaming
Just for Fun
Food and Drink
Photo
Mobile
Chat
File Sharing
Events
Alerts
Travel
Fashion
Video
Education
Music
Money
Utility
Politics
Business
Sports
Classified
All Proportion of Application w/ >25K Active Users
0% 2% 4% 6% 8%
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The Top 40 - Week Ending October 5
Application Vendor Review Count % Active Installs Active Users Active Last WoW ROC
1 Top Friends Slide 2,708 16% 18,187,625 2,746,678 2,673,050 3%
2 FunWall Slide 682 22% 8,998,329 1,911,298 1,383,276 38%
3 Super Wall RockYou! 1,155 11% 10,183,200 1,083,079 820,878 32%
4 SuperPoke! Slide 3,601 10% 10,143,845 950,640 879,749 8%
5 Video Facebook 1,584 9% 10,771,730 936,327 905,353 3%
6 X Me RockYou! 2,263 10% 8,918,763 814,035 550,285 48%
7 iLike iLike 3,791 8% 9,396,575 730,953 736,549 -1%
8 Movies Flixster 1,520 7% 9,158,657 580,201 705,972 -18%
9 Graffiti Mark Kantor;;Tim Suzman;;Ted Suzman 5,469 7% 8,028,517 514,692 528,802 -3%
10 Likeness RockYou! 1,339 6% 9,418,350 499,705 429,721 16%
11 My Questions Slide 1,105 5% 9,783,925 417,009 441,958 -6%
12 Quizzes Eric Diep;;Joe Winterhalter 1,459 9% 4,402,856 363,478 286,168 27%
13 Mobile Facebook 755 16% 2,268,627 345,282 349,442 -1%
14 Free Gifts Zachary Allia 5,132 5% 7,342,580 338,662 373,674 -9%
15 Booze Mail Renkoo 1,840 8% 4,257,171 330,494 352,483 -6%
16 Compare People Ivko Maksimovic 7,252 4% 7,939,500 319,212 383,516 -17%
17 Honesty Box Dan Peguine;;Erik Giberti 4,402 9% 3,445,614 279,311 285,829 -2%
18 (fluff)Friends Mike Sego 22,938 13% 2,221,192 278,794 266,123 5%
19 Vampires Blake Commagere;;AJ Olson 2,013 8% 3,535,325 274,808 293,658 -6%
20 Scrabulous Rajat Agarwalla;;Jayant Agarwalla 3,363 33% 869,706 270,175 237,862 14%
21 Moods Drew Lustro;;Amit Matani 871 5% 5,825,860 265,452 272,839 -3%
22 Causes Tam Vo;;Blake Commagere 1,302 5% 5,426,880 251,224 251,402 0%
23 Superlatives Jamal Ashraf;;Suleman Ali 511 5% 5,511,900 249,760 261,705 -5%
24 My Aquarium Greg Thomson 3,072 6% 3,771,780 219,672 216,450 1%
25 Grow-a-Gift Mike Mangino;;Keith Schacht 1,616 9% 2,316,100 207,010 181,518 14%
26 Naughty Gifts Going 1,498 6% 3,633,500 200,999 255,536 -21%
27 Hatching Eggs Mike Mangino;;Keith Schacht 596 13% 1,691,536 200,470 170,227 18%
28 Zombies Blake Commagere;;AJ Olson 2,500 5% 4,259,220 197,133 220,217 -10%
29 Sticky Notes J-Squared Media 1,175 5% 4,055,860 195,330 211,012 -7%
30 Entourage Chris Osburne;;Vito Nonni 61 10% 2,117,190 194,763 199,172 -2%
31 Nicknames Adam Gries;;Wayne Mak 171 7% 3,091,120 184,524 202,380 -9%
32 Are YOU Interested? eTwine Holdings 442 10% 1,891,900 172,649 155,868 11%
33 Fortune Cookie Slide 1,293 3% 5,869,067 162,215 169,517 -4%
34 Texas HoldEm Poker Eric Schiermeyer;;Mark Pincus 2,262 6% 2,915,200 150,093 154,107 -3%
35 WereWolves Blake Commagere;;AJ Olson 968 8% 1,873,263 147,828 156,196 -5%
36 Bumper Sticker Harris Tsim;;Samuel Adams 595 11% 1,323,182 135,241 114,634 18%
37 Fight Club Wayne Ellis 471 32% 493,188 133,017 103,231 29%
38 Advanced Wall Phil Gibbons 152 4% 3,671,233 131,657 110,102 20%
39 PacMan thewurld 804 12% 1,219,564 129,955 120,910 7%
40 Favorite Peeps! Slide 2,511 5% 2,755,620 126,193 135,339 -7%
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A Web 2.0 Refresher
Tim O’Reilly
O’Reilly Media, Inc.
www.oreilly.com
Graphing Social Networks
October 9, 2007

User Generated
Sharing Openness
Content
Blogs Social
Networks
Wikis
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User Generated
Sharing Openness
Content
Blogs Social
Networks
Wikis
Love
Peace
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What Really Distinguishes Web 2.0
Systems that harness network effects to
get better the more people use them.
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Building a Collective Database
• Building on top of open source, Yahoo! pays
people to build its directory
• Learning from open source, Wikipedia uses
volunteers
• P2P file sharing users build song swapping
network as a byproduct of their own self-interest
• (Google works this way, and so does Facebook)
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Harnessing Collective Intelligence
Every true Web 2.0 company is building a
database whose value grows in proportion to
the number of participants -- that is, a
network-effect-driven data lock-in -- with
accelerating returns to the winners.
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“Red Shift”
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34

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The opportunity was in finding new
meaning in user-generated data,
and turning that meaning into real-
time user-facing services
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40

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Why Should I Have To Confirm?
• geni.com already knows that Sean is my
brother
• My company directory already knows who
works at O’Reilly
• Google knows that I worked with Danese
Cooper on open source Java and that she
has spoken at many of my conferences
• Amazon knows who’s written books for me
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How Ridiculous Is This?
• Dialed calls (last 10)
• Received calls (last 10)
• Missed calls (last 10)
My phone and my email already know who
my friends are?
Social Networking has a long way to go till
it’s the Web 2.0 address book
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How Ridiculous Is This?
• “Are you my friend?”
(Anyone with a communications network -
email, phone, or IM - already knows who my
friends are!)
Where is the Web 2.0 address book?
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The Internet Operating System
The subsystems will be data subsystems
– Location
– Identity
– Time
– Products
– Media types
– Relationships
– Price
– Tags
– ???
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A Platform Beats an Application
Every Time
•Lotus 1-2-3
•WordPerfect
•Netscape Navigator
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A Platform Beats an Application
Every Time
•Lotus 1-2-3
Microsoft Excel
•WordPerfect
Microsoft Word
•Netscape Internet Explorer
Microsoft Navigator
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A Platform Beats an Application
Every Time
Microsoft Excel
Microsoft Word
Microsoft Internet Explorer
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Two Types of Platform
• One Ring to Rule Them All
• Small Pieces Loosely Joined
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Questions You Should Be Asking
• Am I doing everything I can to build
applications that learn from my users?
• Does my application get better with more
users, or just more busy and more crowded?
• If “Data is the Intel Inside” of Web 2.0, what
data do I own?
• What user-facing services can I build against
it?
• Does my platform give me and my users
control, or take it away from us?
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What I Want From the
Social Graph
Tim O’Reilly
O’Reilly Media, Inc.
www.oreilly.com
Graphing Social Networks
October 9, 2007

Some Things I Want From Social
Networking
• I want it to reflect my REAL social
relationships (mine my phone and email)
• I want it to help me manage those contacts
(how to reach them, updated status)
• I want to manage groups of people
• I want it to recognize asymmetry in
relationships
• I want fine grained control over what I see
and what I ignore
• I want to discover interesting people
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Doesn’t Fit My Relationships...
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Smart Presence on the Phone
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“I’m an inventor.
I became interested in
long term trends because
an invention has to make
sense in the world in
which it is finished, not
the world in which it is
started.”
-Ray Kurzweil
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For More Information
• What is Web 2.0?
http://www.oreillynet.com/go/web2
• http://tim.oreilly.com
• http://radar.oreilly.com
• http://labs.oreilly.com
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