A 61-million-person experiment insocial influence and politicalmobilizationRobert M. Bond, Christopher J. Fariss, Janson J...
Outline• Main Results• Technical Details
Main Results• A randomized controlled trial• > 18 years old, U.S.• Nov. 2nd, 2010 – U.S. congressional election.
Main Results• Three groups of users ▫ “social message”    n = 60,055,176 (99%) ▫ “informational”    n = 611,096 (1%) ▫ “...
Main Results
Main Results   polling places
Main Results   self-reported voting
Main Results   social message
Main Results
Main Results
Main Results   20.04% vs. 17.96%
Main Results• Self-expression + information seeking
Main Results• Self-expression + information seeking                 No guarantee!
Main Results• Self-expression + information seeking                 No guarantee!• Match with public voting records
Main Results• social message vs. no message: 0.39%
Main Results• social message vs. informational message: 0.39%
Main Results• informational message vs. no message: 0.00%
Main Results
Main Results• 149 friends on average• Strong ties           behavioral effect?
Main Results• Divide types of interactions by decile• High-level interactions mean close friends?
Main Results
Main Results• Compare            Social message   No message
Main Results
Main Results
Main Results
Main Results
Main Results
Main Results• Close friends matter.
Main Results• Something real?
Main Results• Something real? ▫ friends: 886,000 expressed votes ▫ close friends: + 559,000 expressed votes ▫ close friend...
Main Results• Something real? friends: ▫ 282,000 validated votes ▫ 74,000 polling-place searches
Main Results• Some context ▫ US midterm elections    36.3% (2002) to 37.2%   (2006) To 37.8% (2010) ▫ 60,000 voters (d) ▫...
Main Results• Claims ▫ Online political mobilization works. ▫ Generate real validate votes.    Contradict previous resear...
Technical Details
Technical Details
Technical Details
Technical Details
Technical Details• Matching to Voting Records ▫   First names + last Names + full birthdates ▫   Cost $0 -> $1500 per stat...
Technical Details• Matching to Voting Records (cont.) ▫ 1/3 matched. ▫ Name conventions.
Technical Details• Overreporting and Underreporting ▫ 3.8% self-reported -> abstained ▫ 50.1% declined to report -> voted•...
Technical Details• Determination of “Close” Friends ▫ Media multiplexity ▫ # interactions of f/ total # of interactions wi...
Technical Details• Network permutation ▫   Keep the network topology fixed ▫   Randomly permute the assignment to treatmen...
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A 61 million-person experiment in social influence and political

  1. 1. A 61-million-person experiment insocial influence and politicalmobilizationRobert M. Bond, Christopher J. Fariss, Janson J.Jones, Jaime E. Settle and James H. FowlerUCSDAdam D. I. Kramer and Cameron MarlowFacebook
  2. 2. Outline• Main Results• Technical Details
  3. 3. Main Results• A randomized controlled trial• > 18 years old, U.S.• Nov. 2nd, 2010 – U.S. congressional election.
  4. 4. Main Results• Three groups of users ▫ “social message”  n = 60,055,176 (99%) ▫ “informational”  n = 611,096 (1%) ▫ “no message”  n = 611,044 (1%)
  5. 5. Main Results
  6. 6. Main Results polling places
  7. 7. Main Results self-reported voting
  8. 8. Main Results social message
  9. 9. Main Results
  10. 10. Main Results
  11. 11. Main Results 20.04% vs. 17.96%
  12. 12. Main Results• Self-expression + information seeking
  13. 13. Main Results• Self-expression + information seeking No guarantee!
  14. 14. Main Results• Self-expression + information seeking No guarantee!• Match with public voting records
  15. 15. Main Results• social message vs. no message: 0.39%
  16. 16. Main Results• social message vs. informational message: 0.39%
  17. 17. Main Results• informational message vs. no message: 0.00%
  18. 18. Main Results
  19. 19. Main Results• 149 friends on average• Strong ties behavioral effect?
  20. 20. Main Results• Divide types of interactions by decile• High-level interactions mean close friends?
  21. 21. Main Results
  22. 22. Main Results• Compare Social message No message
  23. 23. Main Results
  24. 24. Main Results
  25. 25. Main Results
  26. 26. Main Results
  27. 27. Main Results
  28. 28. Main Results• Close friends matter.
  29. 29. Main Results• Something real?
  30. 30. Main Results• Something real? ▫ friends: 886,000 expressed votes ▫ close friends: + 559,000 expressed votes ▫ close friends of close friends: + 1M expressed votes
  31. 31. Main Results• Something real? friends: ▫ 282,000 validated votes ▫ 74,000 polling-place searches
  32. 32. Main Results• Some context ▫ US midterm elections  36.3% (2002) to 37.2% (2006) To 37.8% (2010) ▫ 60,000 voters (d) ▫ 280,000 voters (i) ▫ 0.14% of 236M in 2010
  33. 33. Main Results• Claims ▫ Online political mobilization works. ▫ Generate real validate votes.  Contradict previous research. ▫ Social mobilization is significantly effective than informational mobilization alone. ▫ Close friends have about four times more influence. ▫ Online social networks influence offline behaviors.
  34. 34. Technical Details
  35. 35. Technical Details
  36. 36. Technical Details
  37. 37. Technical Details
  38. 38. Technical Details• Matching to Voting Records ▫ First names + last Names + full birthdates ▫ Cost $0 -> $1500 per state ▫ Exclude Texas ▫ Include  Arkansas, California, Connecticut, Florida, Kansas, Kentucky, Missouri, Nevada, New Jersey, New York, Oklahoma, Pennsylvania and Rhode Island ▫ 40% of all registered votes -> 6,338,882 voters and abstainers.
  39. 39. Technical Details• Matching to Voting Records (cont.) ▫ 1/3 matched. ▫ Name conventions.
  40. 40. Technical Details• Overreporting and Underreporting ▫ 3.8% self-reported -> abstained ▫ 50.1% declined to report -> voted• Social message vs. informational message ▫ 0.99% more likely to overreport to voting ▫ 4.19% less likely to underreport voting
  41. 41. Technical Details• Determination of “Close” Friends ▫ Media multiplexity ▫ # interactions of f/ total # of interactions with all ▫ Divide by decile. ▫ Each decile is a subset of the previous one. ▫ Validated via survey.
  42. 42. Technical Details• Network permutation ▫ Keep the network topology fixed ▫ Randomly permute the assignment to treatment ▫ Repeat 1,000 times ▫ Theoretical null distribution

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