Web 2.0 Expo San Francisco April 3, 2009 INFLUENCE Gregor Hochmuth dotgrex.com / @grex Finding and applying
Web 2.0 Expo San Francisco April 3, 2009 Gregor Hochmuth dotgrex.com * This is  not  a Google presentation. This is indepe...
We need new models for understanding what’s interesting
We need new models for understanding what’s interesting (right now)
While some have been busy building  “recommender systems”  for the last 20 years …
…  others just brought our best recommender system online:
People we know
People we  trust
People we  #follow
We don’t need machines anymore to tell us what’s interesting.
Our friends do that now.
The  new  problem is:
Making machines understand what’s interesting
Making machines understand  who’s  interesting
Making machines understand who’s  important
Making machines understand who’s  connected
Making machines understand who’s  safe to ignore
Making machines understand  INFLUENCE
Understanding influence   ↓   who’s interesting    ↓   what’s interesting
Understanding influence   ↓   who’s interesting     ↓   what’s interesting
Understanding influence   ↓   who’s interesting    ↓   what’s interesting
Understanding influence    ↓   interesting people     ↓   interesting content
Understanding influence    ↓   interesting people     ↕     interesting content
We need new models for understanding what’s interesting (right now)
We need new models for understanding what’s interesting right now
sort by:   Most Recent
 
 
 
 
 
sort by:   Most Recent
sort by:   Most Recent
 
sort by:   Most Recent
sort by:   Most interesting
sort by:   Most timely
sort by:   Most influential
Influencers have things to spread
Influencers have things to spread.
Influencers are everywhere.
Influencers are everyday people.
Influencers are in every social circle.
But influencers  need … people who listen
 
people who listen.
people who follow them.
= Audience
Audience
Audience
Audience
Audience
audience :  a common  understanding of who’s listening
audience :  a common  understanding of who’s listening
vs.
vs.
vs. I know my audience I know some numbers
<ul><li>Evidence of understanding of audience  on Twitter: @replies RTs </li></ul>
latest redesign?   supports a better model of audience
latest redesign?   supports a better model of audience
latest redesign?   supports a better model of audience >  you see  everyone’s   updates now
 
Feedback Letting people know their content matters
Ownership Letting people know who contributed what
Serendipity Letting people extend their networks without effort
 
Analyzing influence
finding the influencers
What makes one person more influential?
How many people listen?
How many people listen?
It’s  who  listens , not how many.
Analyzing influence
Analyzing influence I’m friends with Shaq!!
Analyzing influence I’m famous I’m friends with Shaq!!
Analyzing influence I’m famous I’m friends with Shaq!! I’m special
Analyzing influence Connector Maven
Analyzing influence: The Twitter example
Analyzing influence: The Twitter example Tim “ Importance”  of Tim is determined by the importance of the people who follo...
Analyzing influence: The Twitter example 8 = importance / # of outgoing connections
Analyzing influence: The Twitter example 8 +  8 / 3 +  8 / 3 +  8 / 3 = importance / # of outgoing connections =  8 / 3
Analyzing influence: The Twitter example 3 = 8/3 + 2/12 + 1/6 = 3 + 8/3 + 2/12 + 1/6
Analyzing influence: The Twitter example 3 = 8/3 + 2/12 + 1/6 + 8/3 + 2/12 + 1/6 + 3/2 + 3/2
Analyzing influence: The Twitter example 3 = 8/3 + 2/12 + 1/6 + 8/3 + 2/12 + 1/6 + 3/2 + 3/2 and  repeat!
“ Honey, this looks familiar—”
“ It’s PageRank, dear. You use it every day.”
Analyze influence wherever people  trade feedback
Analyze influence wherever people  exchange something
Analyze influence wherever people  exchange something asymmetry  is your friend!
Analyze influence wherever people  exchange something asymmetry  is your friend! the opposite may not be true.
Follows try it on Twitter
Favorites, Likes try it on Flickr
Messages, Comments try it on Facebook
Ratings try it on Amazon, Yelp
So. Understanding Influence:
Use it for ranking
Use it for ranking
Use it for sorting
Use it for discovery
Use it for reducing the noise
Web 2.0 Expo San Francisco April 3, 2009 INFLUENCE Gregor Hochmuth dotgrex.com / @grex thanks.
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Finding & Analyzing Influence (Gregor Hochmuth) - Web 2.0 Expo San Francisco -

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Session from Web 2.0 Expo San Francisco, April 3, 2009

Finding Influence: Design Patterns for Smarter Crowds

Who’s important and how do I know? Who has the scoop and how will I find out? In any of your network of connections, some people are more interesting to you than others. Influence is about applying that understanding at large scale to the content people share and knowing who’s interesting.

http://www.web2expo.com/webexsf2009/public/schedule/detail/7796

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  • Finding & Analyzing Influence (Gregor Hochmuth) - Web 2.0 Expo San Francisco -

    1. 1. Web 2.0 Expo San Francisco April 3, 2009 INFLUENCE Gregor Hochmuth dotgrex.com / @grex Finding and applying
    2. 2. Web 2.0 Expo San Francisco April 3, 2009 Gregor Hochmuth dotgrex.com * This is not a Google presentation. This is independent pondering prior to my current work at Google.
    3. 3. We need new models for understanding what’s interesting
    4. 4. We need new models for understanding what’s interesting (right now)
    5. 5. While some have been busy building “recommender systems” for the last 20 years …
    6. 6. … others just brought our best recommender system online:
    7. 7. People we know
    8. 8. People we trust
    9. 9. People we #follow
    10. 10. We don’t need machines anymore to tell us what’s interesting.
    11. 11. Our friends do that now.
    12. 12. The new problem is:
    13. 13. Making machines understand what’s interesting
    14. 14. Making machines understand who’s interesting
    15. 15. Making machines understand who’s important
    16. 16. Making machines understand who’s connected
    17. 17. Making machines understand who’s safe to ignore
    18. 18. Making machines understand INFLUENCE
    19. 19. Understanding influence ↓ who’s interesting ↓ what’s interesting
    20. 20. Understanding influence ↓ who’s interesting ↓ what’s interesting
    21. 21. Understanding influence ↓ who’s interesting ↓ what’s interesting
    22. 22. Understanding influence ↓ interesting people ↓ interesting content
    23. 23. Understanding influence ↓ interesting people ↕ interesting content
    24. 24. We need new models for understanding what’s interesting (right now)
    25. 25. We need new models for understanding what’s interesting right now
    26. 26. sort by: Most Recent
    27. 32. sort by: Most Recent
    28. 33. sort by: Most Recent
    29. 35. sort by: Most Recent
    30. 36. sort by: Most interesting
    31. 37. sort by: Most timely
    32. 38. sort by: Most influential
    33. 39. Influencers have things to spread
    34. 40. Influencers have things to spread.
    35. 41. Influencers are everywhere.
    36. 42. Influencers are everyday people.
    37. 43. Influencers are in every social circle.
    38. 44. But influencers need … people who listen
    39. 46. people who listen.
    40. 47. people who follow them.
    41. 48. = Audience
    42. 49. Audience
    43. 50. Audience
    44. 51. Audience
    45. 52. Audience
    46. 53. audience : a common understanding of who’s listening
    47. 54. audience : a common understanding of who’s listening
    48. 55. vs.
    49. 56. vs.
    50. 57. vs. I know my audience I know some numbers
    51. 58. <ul><li>Evidence of understanding of audience on Twitter: @replies RTs </li></ul>
    52. 59. latest redesign? supports a better model of audience
    53. 60. latest redesign? supports a better model of audience
    54. 61. latest redesign? supports a better model of audience > you see everyone’s updates now
    55. 63. Feedback Letting people know their content matters
    56. 64. Ownership Letting people know who contributed what
    57. 65. Serendipity Letting people extend their networks without effort
    58. 67. Analyzing influence
    59. 68. finding the influencers
    60. 69. What makes one person more influential?
    61. 70. How many people listen?
    62. 71. How many people listen?
    63. 72. It’s who listens , not how many.
    64. 73. Analyzing influence
    65. 74. Analyzing influence I’m friends with Shaq!!
    66. 75. Analyzing influence I’m famous I’m friends with Shaq!!
    67. 76. Analyzing influence I’m famous I’m friends with Shaq!! I’m special
    68. 77. Analyzing influence Connector Maven
    69. 78. Analyzing influence: The Twitter example
    70. 79. Analyzing influence: The Twitter example Tim “ Importance” of Tim is determined by the importance of the people who follow Tim.
    71. 80. Analyzing influence: The Twitter example 8 = importance / # of outgoing connections
    72. 81. Analyzing influence: The Twitter example 8 + 8 / 3 + 8 / 3 + 8 / 3 = importance / # of outgoing connections = 8 / 3
    73. 82. Analyzing influence: The Twitter example 3 = 8/3 + 2/12 + 1/6 = 3 + 8/3 + 2/12 + 1/6
    74. 83. Analyzing influence: The Twitter example 3 = 8/3 + 2/12 + 1/6 + 8/3 + 2/12 + 1/6 + 3/2 + 3/2
    75. 84. Analyzing influence: The Twitter example 3 = 8/3 + 2/12 + 1/6 + 8/3 + 2/12 + 1/6 + 3/2 + 3/2 and repeat!
    76. 85. “ Honey, this looks familiar—”
    77. 86. “ It’s PageRank, dear. You use it every day.”
    78. 87. Analyze influence wherever people trade feedback
    79. 88. Analyze influence wherever people exchange something
    80. 89. Analyze influence wherever people exchange something asymmetry is your friend!
    81. 90. Analyze influence wherever people exchange something asymmetry is your friend! the opposite may not be true.
    82. 91. Follows try it on Twitter
    83. 92. Favorites, Likes try it on Flickr
    84. 93. Messages, Comments try it on Facebook
    85. 94. Ratings try it on Amazon, Yelp
    86. 95. So. Understanding Influence:
    87. 96. Use it for ranking
    88. 97. Use it for ranking
    89. 98. Use it for sorting
    90. 99. Use it for discovery
    91. 100. Use it for reducing the noise
    92. 101. Web 2.0 Expo San Francisco April 3, 2009 INFLUENCE Gregor Hochmuth dotgrex.com / @grex thanks.
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