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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 independent pondering prior to my current work at Google.
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
[object Object]
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 follow Tim.
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 -