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Social Networks 101

Social Networks 101. Prof. Jason Hartline and Prof. Nicole Immorlica. Evaluate your peers. Experiment : Q . How many points were earned in the first week of class? Write your answer on your index cards and pass it to your TAs. Lecture Seven : Structural balance and

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Social Networks 101

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  1. Social Networks 101 Prof. Jason Hartline and Prof. Nicole Immorlica

  2. Evaluate your peers Experiment: Q. How many points were earned in the first week of class? Write your answer on your index cards and pass it to your TAs.

  3. Lecture Seven: Structural balance and wisdom of the crowds

  4. Lecture Seven, Part One: Structural balance

  5. The enemy of my enemy

  6. … is my friend.

  7. Signed graphs + - Friends Enemies

  8. Three-node signed graphs Balanced + + - - + - + - - - + + Unbalanced

  9. Balanced or not? + - - - + - - - + + + -

  10. In real life …

  11. 1907 UK Austria-Hungary WWI France Germany Russia Italy

  12. And a bit later … Why did the US support Pakistan in the Bangladeshi war of independence?

  13. Where is Bangladesh?

  14. 1970s US Pakistan ? Bangladesh Soviet Union China India

  15. Structural balance What do balanced networks look like?

  16. Suppose all people know each other.

  17. Complete networks Definition. A network is complete if all people know each other.

  18. Complete networks Definition. A network is complete if all people know each other.

  19. Balanced networks Definition. A complete network is balanced if all triangles are balanced.

  20. Structural balance In a complete balanced network, either or - B A + + + all people like each other there are two opposing camps

  21. Pick any node: Argument. a Define: 1. Every two nodes in A are friends A = all friends of a B = all enemies of a 2. Every two nodes in B are friends 3. Every node in A is an enemy of every node in B

  22. Argument. a B = all enemies of a A = all friends of a there are two opposing camps

  23. Argument. a B = all enemies of a A = all friends of a Or everyone is friends if a has no enemies.

  24. Optional material Generalizing to arbitrary graphs.

  25. Lecture Seven, Part Two: Wisdom of the crowds

  26. Collective intelligence The average of our beliefs is a very close approximation to the truth. Closer than any individual belief!

  27. Who wants to be a millionaire? Audience lifeline – 91% right Call-an-expert – 65% right Wisdom of the crowds, J. Surowiecki

  28. Jan. 28, 1986

  29. Challenger explosion Wisdom of the crowds, J. Surowiecki

  30. When it works Diversity of opinion Each person should have private information even if it's just an eccentric interpretation of the known facts.

  31. When it works Independence People's opinions aren't determined by the opinions of those around them.

  32. When it works Decentralization People are able to specialize and draw on local knowledge.

  33. When it works Aggregation Some mechanism exists for turning private judgments into a collective decision.

  34. Explanation Each person has their own personal noisy signal of the truth (diversity, independence, decentralization). By aggregating, we cancel out the noise, and the truth is revealed.

  35. Time for Math Corner

  36. Evaluate your peers Experiment: Q. How many points were earned in the first week of class? A. 540.21 points.

  37. Next time Information cascades

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