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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

7
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

9
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



10
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
             7
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


12
87% of Usage Goes to 2% of Apps




13
The Top 50 Developers by Usage




14
- 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




15
Safari Views vs. Bookscan Unit Sales



                         Additional demand from the
                                long tail effect
A Power Law Distribution




17
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)




18
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



19
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%



22
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



23
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%




24
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%

25
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




27
User Generated
     Sharing    Openness
                           Content



     Blogs                        Social
                                  Networks

        Wikis
                              Love
                  Peace




28
29
What Really Distinguishes Web 2.0

     Systems that harness network effects to
     get better the more people use them.




30
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)




31
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.




32
“Red Shift”




33
34
35
The opportunity was in finding new
      meaning in user-generated data,
     and turning that meaning into real-
          time user-facing services




36
37
38
39
40
41
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




42
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


43
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?




44
45
The Internet Operating System

     The subsystems will be data subsystems
       – Location
       – Identity
       – Time
       – Products
       – Media types
       – Relationships
       – Price
       – Tags
       – ???

46
A Platform Beats an Application
                 Every Time

     •Lotus 1-2-3
     •WordPerfect
     •Netscape Navigator




47
A Platform Beats an Application
                 Every Time

     •Lotus 1-2-3
      Microsoft Excel
     •WordPerfect
      Microsoft Word
     •Netscape Internet Explorer
      Microsoft Navigator




47
A Platform Beats an Application
                Every Time

     Microsoft Excel
     Microsoft Word
     Microsoft Internet Explorer




47
Two Types of Platform
     • One Ring to Rule Them All




     • Small Pieces Loosely Joined




48
49
50
51
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?

52
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

54
55
56
57
58
59
60
61
62
Doesn’t Fit My Relationships...




63
64
65
66
67
Smart Presence on the Phone




68
“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




69
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




70

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The Facebook Application Market, by Tim Oreilly

  • 1. The Facebook Application Market Tim O’Reilly O’Reilly Media, Inc. www.oreilly.com Graphing Social Networks October 9, 2007
  • 2. We’re best known as a book publisher 2
  • 3. What We Really Do At O'Reilly Change the world by spreading the knowledge of innovators 3
  • 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 4
  • 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 5
  • 6. 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
  • 7. 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 7
  • 8. Facebook is the new frontier What is it telling us? 8
  • 9. 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 9
  • 10. 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 10
  • 11. 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 7
  • 12. 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 12
  • 13. 87% of Usage Goes to 2% of Apps 13
  • 14. The Top 50 Developers by Usage 14
  • 15. - 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 15
  • 16. Safari Views vs. Bookscan Unit Sales Additional demand from the long tail effect
  • 17. A Power Law Distribution 17
  • 18. 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) 18
  • 19. 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 19
  • 20. 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
  • 21. 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
  • 22. 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% 22
  • 23. 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 23
  • 24. 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% 24
  • 25. 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% 25
  • 26. A Web 2.0 Refresher Tim O’Reilly O’Reilly Media, Inc. www.oreilly.com Graphing Social Networks October 9, 2007
  • 27. User Generated Sharing Openness Content Blogs Social Networks Wikis 27
  • 28. User Generated Sharing Openness Content Blogs Social Networks Wikis Love Peace 28
  • 29. 29
  • 30. What Really Distinguishes Web 2.0 Systems that harness network effects to get better the more people use them. 30
  • 31. 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) 31
  • 32. 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. 32
  • 34. 34
  • 35. 35
  • 36. The opportunity was in finding new meaning in user-generated data, and turning that meaning into real- time user-facing services 36
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  • 42. 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 42
  • 43. 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 43
  • 44. 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? 44
  • 45. 45
  • 46. The Internet Operating System The subsystems will be data subsystems – Location – Identity – Time – Products – Media types – Relationships – Price – Tags – ??? 46
  • 47. A Platform Beats an Application Every Time •Lotus 1-2-3 •WordPerfect •Netscape Navigator 47
  • 48. A Platform Beats an Application Every Time •Lotus 1-2-3 Microsoft Excel •WordPerfect Microsoft Word •Netscape Internet Explorer Microsoft Navigator 47
  • 49. A Platform Beats an Application Every Time Microsoft Excel Microsoft Word Microsoft Internet Explorer 47
  • 50. Two Types of Platform • One Ring to Rule Them All • Small Pieces Loosely Joined 48
  • 51. 49
  • 52. 50
  • 53. 51
  • 54. 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? 52
  • 55. What I Want From the Social Graph Tim O’Reilly O’Reilly Media, Inc. www.oreilly.com Graphing Social Networks October 9, 2007
  • 56. 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 54
  • 57. 55
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  • 64. 62
  • 65. Doesn’t Fit My Relationships... 63
  • 66. 64
  • 67. 65
  • 68. 66
  • 69. 67
  • 70. Smart Presence on the Phone 68
  • 71. “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 69
  • 72. 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 70