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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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

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

Twitter

Favorites, Likes

try it on

Flickr

Messages, Comments

try it on

Facebook

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.

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