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What Is A Network? (and why do we care?)

What Is A Network? (and why do we care?). Network Defined. “A collection of objects (nodes) connected to each other in some fashion” - Watts, 2002. In A Network …. An agent/object's actions are affected by the actions of others around it.

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What Is A Network? (and why do we care?)

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  1. What Is A Network?(and why do we care?)

  2. Network Defined • “A collection of objects (nodes)connectedto each other in some fashion” - Watts, 2002

  3. In A Network … • An agent/object's actions are affected by the actions of othersaround it. • Actions/choices arenot made in isolation,i.e., they arecontingent on the actions and choices of others

  4. Examples of Networks • The Internet • Neural Networks (computer & human) • Proteins and Genes • Stem cells (and other cells) • Diseases • Social Groups

  5. Networks • Theory-> from “fixed” to “dynamic” • “real networks represent populations of individual components that are actually doing something” - Watts, 2002 • Networks are key to understanding non-linear, dynamic systems

  6. Data Networks Britain From Above (http://www.bbc.co.uk/britainfromabove)

  7. Terms • Node = individual components of a network, e.g. people, power stations, links • Edge = direct link between components (referred to as a dyad in context of social networks, a relationship between two people) • Path = route taken to connect two nodes. “Six degrees of separation” average path length = 6

  8. Human Networks http://blog.linkedin.com/2011/01/24/linkedin-inmaps/

  9. Milgram’s Experiment • Began in 1967 at Harvard University • Sent packages to randomly selected people in Omaha, Nebraska & Wichita and asked that they be delivered to individuals in Boston, Massachusetts • Could only forward to people they knew on a first-name basis • 64 of 296 letters reached their destination • Average path length of these was around 5.5 or 6

  10. Unclustered Network

  11. Clustered Network

  12. Grid/lattice network(structure, order) • Small-world network(a mix of order and randomness) • Random network(randomness) Types of Networks

  13. Power Law

  14. Shirky On Power Law • Power law distributions tend to arise in social systems where many people express their preferences among many options. • As the number of options rise, the curve becomes more extreme. • Most elements in a power law system are below average (the “long tail”)

  15. Shirky On Power Law “Alice, the first user, chooses her blogs unaffected by anyone else, but Bob has a slightly higher chance of liking Alice's blogs than the others. When Bob is done, any blog that both he and Alice like has a higher chance of being picked by Carmen, and so on, with a small number of blogs becoming increasingly likely to be chosen in the future because they were chosen in the past.”

  16. Networks : Weak Ties • “Within a social network, weak ties …are indispensable to individuals’ opportunities and to their incorporation into communities while strong ties breed local cohesion.”(Mark Granovetter, 1973)

  17. Networks : Weak Ties • The stronger the tie between two people, the more similar they are, in various ways (Mark Granovetter, 1973) • Weak ties = “friends of friends” • Weak ties provide a bridge between social circles, access to information and resources beyond my “tight” social circle

  18. Weak Ties Are Powerful • “On average, the first 5 random re-wirings reduce the average path length of the network by one-half, regardless of the size of the network” [Watts, 2002]

  19. Strong Tie Truism • Over time, we are more likely to become acquainted if we have something in common • this bias towards the familiar reduces the pure randomness of connections • “homophily” or “birds of a feather flock together”

  20. California: F500 Companies http://flickr.com/photos/11242012@N07/1363558436

  21. TheyRule.Net

  22. Informal Properties : The Web • Large scale • Continual growth • Distributed, organic growth: vertices “decide” who to link to • A mixture of local and long-distance connections • Interaction (largely) restricted to links • Abstract notions of distance: geographical, content, social…

  23. Discussion • Reaction to “your friends have more friends than you do” (friends paradox - TED talk) • What does a highly “spreadable” (viral) idea look like? (RickRolling as a meme) • How might we actively seek new ideas/voices? What is the role of software here?

  24. Credits • Kathy E Gill, @kegill, CC share-share-alike, non-commercial • Sources: • Duncan Watts, Six Degrees of Separation • Kyle Findlay, SAMRA 2010 Conference presentation • Michael Kearns, Social Network Theory

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