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CGT talk atInfopresse
      @cgtheoret
La Révolution des données sociales
Every minute:

• 48 hours of video are downloaded on Youtube
• 320 new accounts and 98,000 tweets appear
  on Twitter
• 168,000,000 million emails are sent
• 20,000 new posts on Tumblr
• 6,600 photos appear on Flickr
• Over 20% of all websites are
  CMS/wordpress/etc…
                    @cgtheoret
@cgtheoret
@cgtheoret
@cgtheoret
@cgtheoret
@cgtheoret
@cgtheoret
@cgtheoret
@cgtheoret
But…
• Facebook has lost 1.5 million users in Canada
  and 6 million in the United States
• Yahoo study: 50% of the content that is read
  and shared by humans is produced by only
  20, 000 accounts



                     @cgtheoret
@cgtheoret
This flood of data isn’t only about the scale that
  is nearly impossible to grasp in human terms.
  Other internal dynamics come into play and
  challenge interpretation . . .




                       @cgtheoret
@cgtheoret
@cgtheoret
This is so complicated, Stanford now offers a
  course on this subject:




                       @cgtheoret
Who is the professor who gives these courses in statistics and
  marketing ?




A physicist, of course…

Andreas Wiegend. Before accepting a position at Stanford, he was the
  Chief Data Scientist at Amazon. He coined the term “Social Data
  Revolution.”


                                 @cgtheoret
Facebook (and Zynga) are sitting on the biggest, most
  detailed sociological database ever created by humankind.
Facebook owns all this data and is not sharing it.
This database is used exclusively to sell advertising and . . . ?




                             @cgtheoret
Hereis the story of a Social Data « Robin Hood » …

                Pete Warden




                        @cgtheoret
Pete Warden was an engineer at Apple when he decided to leave
  and create a start up . . .


The start up didn’t work out. So in his spare time, he developed a
  legal Facebook crawler using their own programming API.


In 2010, his crawler had been operating for 6 months and had
   gathered information on 215 million users that he organized
   according to city, state, etc., while maintaining users’
   anonymity.




                             @cgtheoret
@cgtheoret
@cgtheoret
@cgtheoret
In 2010, LinkedIn hired a team of
17 people to do the same thing:




                      @cgtheoret
But can one “normal” person or company make
  sense of this mass of data without having
  access to teams of experts and an enormous
  budget?

Hundreds of social media monitoring tools are
 available:

195 tools here:

http://www.salesrescueteam.com/social-media-measurement-tools/



                                @cgtheoret
There is even a wiki with 224 tools:
  http://wiki.kenburbary.com/




                            @cgtheoret
But even with the huge success of some
  monitoring companies:

Radian6: $326 million / revenue ~ $20 Million
Sysomos: $34 million / revenue ~ $2 Million
Scoutlabs: $20 million / revenue ~ $1 Million
Postrank: bought by Google, BackType: bought
  by Twitter, etc . . .




                      @cgtheoret
@cgtheoret
@cgtheoret
Monitoring / Analysis
• Monitoring tools present social network
  data in Excel tables:

   – As a list of “nodes” i.e., blog posts, tweets,
     etc.
   – In sequential order by date, one after the
     other
   – The emphasis is on real time
   – This works for a few dozen or hundred . . .
     but what about thousands of posts?

   – Making sense of all those posts is very
     expensive and labour intensive



                                @cgtheoret
Monitoring / Analysis
• The added value of social media
  is not in raw data, but in
  connections between people

And between ideas
• On a fundamental level, it is a
  network
• …and a network = relations

• To understand a network, you
  have to understand its relations

• To understand a single element in
  the network, you have to
  understand its context

                          @cgtheoret
With the “Social Graph” we can calculate “who
 is talking to whom,” “who is connected with
 whom,” and possibly where.

But we can go even further than that . . . .




                       @cgtheoret
With more information and calculations, we can
  see what interests people and how their
  interests are linked.
This is Facebook’s second challenge: ”The
  interest graph.”

How are ideas and conversations connected in
 the social web?



                     @cgtheoret
@cgtheoret
Zeitgeist




  @cgtheoret
Zeitgeist




  @cgtheoret
“The spirit of our times”

“Spirit” and “our times”: two concepts that are
 hard to measure . . . all the more so when you
                combine them . . .




                     @cgtheoret
@cgtheoret
@cgtheoret
@cgtheoret
@cgtheoret
So what exactly is an “interest graph”?

Here’s a concrete example.

Take Réjean . . .

6’2’’, 35 years old, married, lives in Val D’Or. . .

According to traditional market research . . .

                         @cgtheoret
@cgtheoret
@cgtheoret
@cgtheoret
@cgtheoret
Why do you need a “special person” to
 understand the social data revolution?




                      @cgtheoret
@cgtheoret
Why do you need a physicist to understand the
 social data revolution?




Because he is not just a physicist!! He
  understands human behaviour . . .

                       @cgtheoret
@cgtheoret
@cgtheoret
@cgtheoret
Thank you!
cg.theoret@nexalogy.com
      @cgtheoret




         @cgtheoret

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Infopresse cgt-english-final

  • 1. CGT talk atInfopresse @cgtheoret La Révolution des données sociales
  • 2. Every minute: • 48 hours of video are downloaded on Youtube • 320 new accounts and 98,000 tweets appear on Twitter • 168,000,000 million emails are sent • 20,000 new posts on Tumblr • 6,600 photos appear on Flickr • Over 20% of all websites are CMS/wordpress/etc… @cgtheoret
  • 11. But… • Facebook has lost 1.5 million users in Canada and 6 million in the United States • Yahoo study: 50% of the content that is read and shared by humans is produced by only 20, 000 accounts @cgtheoret
  • 13. This flood of data isn’t only about the scale that is nearly impossible to grasp in human terms. Other internal dynamics come into play and challenge interpretation . . . @cgtheoret
  • 16. This is so complicated, Stanford now offers a course on this subject: @cgtheoret
  • 17. Who is the professor who gives these courses in statistics and marketing ? A physicist, of course… Andreas Wiegend. Before accepting a position at Stanford, he was the Chief Data Scientist at Amazon. He coined the term “Social Data Revolution.” @cgtheoret
  • 18. Facebook (and Zynga) are sitting on the biggest, most detailed sociological database ever created by humankind. Facebook owns all this data and is not sharing it. This database is used exclusively to sell advertising and . . . ? @cgtheoret
  • 19. Hereis the story of a Social Data « Robin Hood » … Pete Warden @cgtheoret
  • 20. Pete Warden was an engineer at Apple when he decided to leave and create a start up . . . The start up didn’t work out. So in his spare time, he developed a legal Facebook crawler using their own programming API. In 2010, his crawler had been operating for 6 months and had gathered information on 215 million users that he organized according to city, state, etc., while maintaining users’ anonymity. @cgtheoret
  • 24. In 2010, LinkedIn hired a team of 17 people to do the same thing: @cgtheoret
  • 25. But can one “normal” person or company make sense of this mass of data without having access to teams of experts and an enormous budget? Hundreds of social media monitoring tools are available: 195 tools here: http://www.salesrescueteam.com/social-media-measurement-tools/ @cgtheoret
  • 26. There is even a wiki with 224 tools: http://wiki.kenburbary.com/ @cgtheoret
  • 27. But even with the huge success of some monitoring companies: Radian6: $326 million / revenue ~ $20 Million Sysomos: $34 million / revenue ~ $2 Million Scoutlabs: $20 million / revenue ~ $1 Million Postrank: bought by Google, BackType: bought by Twitter, etc . . . @cgtheoret
  • 30. Monitoring / Analysis • Monitoring tools present social network data in Excel tables: – As a list of “nodes” i.e., blog posts, tweets, etc. – In sequential order by date, one after the other – The emphasis is on real time – This works for a few dozen or hundred . . . but what about thousands of posts? – Making sense of all those posts is very expensive and labour intensive @cgtheoret
  • 31. Monitoring / Analysis • The added value of social media is not in raw data, but in connections between people And between ideas • On a fundamental level, it is a network • …and a network = relations • To understand a network, you have to understand its relations • To understand a single element in the network, you have to understand its context @cgtheoret
  • 32. With the “Social Graph” we can calculate “who is talking to whom,” “who is connected with whom,” and possibly where. But we can go even further than that . . . . @cgtheoret
  • 33. With more information and calculations, we can see what interests people and how their interests are linked. This is Facebook’s second challenge: ”The interest graph.” How are ideas and conversations connected in the social web? @cgtheoret
  • 37. “The spirit of our times” “Spirit” and “our times”: two concepts that are hard to measure . . . all the more so when you combine them . . . @cgtheoret
  • 42. So what exactly is an “interest graph”? Here’s a concrete example. Take Réjean . . . 6’2’’, 35 years old, married, lives in Val D’Or. . . According to traditional market research . . . @cgtheoret
  • 47. Why do you need a “special person” to understand the social data revolution? @cgtheoret
  • 49. Why do you need a physicist to understand the social data revolution? Because he is not just a physicist!! He understands human behaviour . . . @cgtheoret
  • 53. Thank you! cg.theoret@nexalogy.com @cgtheoret @cgtheoret

Notas del editor

  1. The Social Data Revolution