web 2.0 expo san francisco april 3, 2009 influence gregor hochmuth dotgrex.com / @grex finding and...
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Web 2.0 Expo San FranciscoApril 3, 2009
INFLUENCE
Gregor Hochmuthdotgrex.com / @grex
Finding and applying
Web 2.0 Expo San FranciscoApril 3, 2009
Gregor Hochmuthdotgrex.com
*This is not aGoogle presentation.This is independent ponderingprior 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 machinesanymore 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 havethings to spread
Influencers havethings to spread.
Influencers areeverywhere.
Influencers areeveryday people.
Influencers arein 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 to you
vs.
vs.
vs.
I know my audience I know some numbers
Evidence of understanding of audience on Twitter:
@repliesRTs
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 knowtheir content matters
Ownership
Letting people knowwho contributed what
Serendipity
Letting people extendtheir networks without effort
Analyzing influence
finding the influencers
What makes one personmore influential?
How many people listen?
How many people listen?
It’s who listens, not how many.
Analyzing influence
I’m friends withShaq!!
Analyzing influence
I’m famou
s
I’m friends withShaq!!
Analyzing influence
I’m famou
s
I’m friends withShaq!!
I’m speci
al
Analyzing influence
Analyzing influence
Connector
Maven
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
Analyzing influence:
The Twitter example
= importance / # of outgoing connections = 8 / 3
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
Analyzing influence:
The Twitter example
+ 3/2
+ 3/2
3 = 8/3 + 2/12 + 1/6
+ 8/3
+ 2/12
+ 1/6
Analyzing influence:
The Twitter example
+ 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
Favorites, Likes
try it on
Flickr
Messages, Comments
try it on
Ratings
try it on
Amazon, Yelp
So. Understanding Influence:
Use it forranking
Use it forranking
Use it forsorting
Use it fordiscovery
Use it forreducing the noise
Web 2.0 Expo San FranciscoApril 3, 2009
INFLUENCE
Gregor Hochmuthdotgrex.com / @grex
thanks.