4. SOCIETY Facebook: The Social Graph
Keith Shepherd's "Sunday Best”. http://baseballart.com/2010/07/shades-of-greatness-a-story-that-needed-to-be-told/
Southampton, Network Science: Introduction July 15, 2011
5. RANDOM NETWORK MODEL
Pál Erdös
(1913-1996)
Erdös-Rényi model (1960)
Connect with probability p
p=1/6 N=10
k ~ 1.5
8. STRUCTURE OF AN ORGANIZATION
SHOW ME HOW THE RANDOMIZED VERSION OF THE COMPANY NETWORK WOULD LOOK
LIKE. Show its degree distribution next to a Poisson form.
Then from here I got to how it really looks like– and discuss how the map was obtained.
Then we can talk about what are the major structural properties of networks
that we must be aware of.
11. ACTOR NETWORK
Let’s make
it legal
Austin Powers:
The spy who
shagged me
Robert Wagner
Wild Things
What Price Glory
Barry Norton
A Few
Good Men
Monsieur
Verdoux
Southampton, Network Science: Introduction July 15, 2011
13. ORIGIN OF SF NETWORKS: Growth and preferential attachment
(1) Networks continuously expand by the
addition of new nodes
GROWTH:
add a new node with m links
WWW : addition of new documents
(2) New nodes prefer to link to highly
connected nodes.
WWW : linking to well known sites
PREFERENTIAL ATTACHMENT:
the probability that a node connects to a
node with k links is proportional to k.
k
P(ki )= i
S jkj
P(k) ~k-3
Barabási & Albert, Science 286, 509 (1999)
28. BONUS: WHY KEVIN BACON?
Did he make the most movies, perhaps?
Kevin Bacon
No. of movies : 46
No. of actors : 1811
Average separation: 2.79
Is Kevin Bacon the
most connected
actor?
List of actors with the most movie credits.
29. BONUS: WHY KEVIN BACON?
Measure the average distance between Kevin Bacon and all other actors.
Kevin Bacon
No. of movies : 46
No. of actors : 1811
Average separation: 2.79
Is Kevin Bacon the
most connected
actor?
876
Kevin Bacon
2.786981
46
1811
Editor's Notes
We are surrounded by systems that are hopelessly complex, from the society, a collection of six billion individuals, to communications systems, that these days link billions of devices, from computers to cell phones. Our very existence is rooted in the ability of thousands of genes to work together in a seamless fashion; our thoughts, reasoning, and comprehension of the world is hidden in the connections between billions of neurons in our brain. These systems, random looking at first, upon close inspection display endless signatures of order and self-organization whose quantification, understanding, prediction and eventually control is the major intellectual challenge for the science of the 21st century
30 Let me show you how this works. Start from the list of a company’s employees, colored based on their location. This happens to be a Hungarian company that has three locations, one on Budapest and two others outside of the city.This is not enough, however: To apply network science, we need a network: we need to know who listens to whom, who is asking for advice from whom. So a social network company, Maven 7, asked each employee: Whom do you ask for advice when it comes to decisions that impact the company, like, restructuring, advancement, and so on?
10 SEC: How would you identify the individuals that matter if you are given the real social network behind a company that are chosen to lead?
10 SEC: How would you identify the individuals that matter if you are given the real social network behind a company that are chosen to lead?
Erdos can be also connected to Kevin Bacon. Erdos plaid with Gene Paterson, in N is a Number (1993).Who played with Sam Rockwell (Box of Moonlight, 1996).Who palyed with Kevin Bacon in Frost/Nixon (2008)What is my Bacon number, what do you think?recent documentary that was eared on Discovery channel, called Connected (2009).
15 SEC: A typical car has about 5000 components. Yet, we rarely think about the need to control each of them independently.Rather, we can rely on three key components: The steering wheel, the gas pedal and the break, to get us anywhere where the car can go.
10 SEC: How would you identify the individuals that matter if you are given the real social network behind a company that are chosen to lead?
30: We can now apply control theory to these systems, identifying who are the control nodes–the people who really drive the company. First I am letting vibrate the individuals who are NOT the control nodes– and you can see, that most individuals are in this category. Including higher management.So now we have the tools to identify the nodes through which you can take a complex system in any desired direction. The question is, what do you with this knowledge? How will you exploit it to take your system, biological, social, or technological, in the direction where you want to go?
30: We now highlight in red the individuals who really control the system. As you can see on this map, they are often the hubs, but not always. Almost none of them is in the higher management, however. But what matters, however, is that we have the tools to address such a complex problem as control in networks. We did not stay at social networks– we applied the tools of control theory to a wide range of networks. So I will leave you with one of the startling conclusions:
Redo the map to make it more professional looking (see previous slide). Redo the visual efect– have the network go from one to the other phase.That is, we start with one network. Then we flip a link and becomes the other one.
TODO:Redo the two networks on the top to make the node sizes uneven. And more professional the whole look.Remove Labels (Critiacaletc):We will call them:Critical: Cannot control the network without them.Redundant: Never needed for controlIntermittent: Play occasional role in control.We may want to create an effect where I show only one class, then the other, and then all of them together.No need for the bifurcation diagram. Tao has the data for this.
TODO:Redo the two networks on the top to make the node sizes uneven. And more professional the whole look.Remove Labels (Critiacaletc):We will call them:Critical: Cannot control the network without them.Redundant: Never needed for controlIntermittent: Play occasional role in control.We may want to create an effect where I show only one class, then the other, and then all of them together.No need for the bifurcation diagram. Tao has the data for this.
TODO:Redo the two networks on the top to make the node sizes uneven. And more professional the whole look.Remove Labels (Critiacaletc):We will call them:Critical: Cannot control the network without them.Redundant: Never needed for controlIntermittent: Play occasional role in control.We may want to create an effect where I show only one class, then the other, and then all of them together.No need for the bifurcation diagram. Tao has the data for this.
10 SEC: How would you identify the individuals that matter if you are given the real social network behind a company that are chosen to lead?
30: This is obvious here, where we colored the nodes based on their rank. The biggest hubs are not the company directors or the CEO. They are not part of the top management. Most are associates, a kind way to say, workers. Who has the biggest influence? The safety and environmental manager. The only person whose job was to visit each location and talk with everyone. He had no links to the higher management. He was passing on information as collected along his trail. He was the oracle, running a gossip center. So fire the guy? Well, he is not the problem. The problem is that higher management failed to put in place proper channels of communication, leaving behind a structural hole, which this fellow filled in. But what does this have to do with control?
Well, you might know Mel Blanc, the famed voice of popular and beloved animated cartoon char- acters like Bugs Bunny, Woody Woodpecker, Daffy Duck, Porky Pig, Tweety Pie, and Sylvester. And those over fifty years old would have seen Tom London, perhaps the most prolific B western movie actor, por- tray countless sheriffs, ranch owners, and henchmen. The rest of the ac- tors on the most-prolific list, however, eluded us. In the end, after some research, we pinned them down. They are all porn stars.