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Who Are Your Friends?
Who do you discuss Important Matters with?
Who do you spend your Free Time with?
Connected
One Pair
Connected
Connected
Many Pairs
Connected
Interconnected
Connected
Social Network
The Power of Friends
Connected
Friends as Data
Friends as Motivators
Friends as Multipliers
Friends as Sensors
The Framingham Heart Study
Connected
Original Cohort
1948
N = 5,209
Offspring Cohort
1971
N = 5,124
Gen 3 Cohort
2002
N ~ ...
Obesity
Clusters
FHS NETWORK
Connected
Three Degrees
Of Association
FHS NETWORK
Connected
HOMOPHILY
Causes of Similarity and Clustering
INFLUENCE CONTEXT
Connected
The Spread
Of Obesity
Connected
FROM 1971 TO 2003
Spread of Obesity
Connected
NA Christakis and JH Fowler, “The Spread of Obesity in a Large Social Network
Over 32 Years,” ...
20011971
Smoking Clusters
FHS NETWORK
Connected
Drinking Clusters
FHS NETWORK
Connected
ANGER HAPPINESS
Reading Emotions
Connected
Happiness
Clusters
FHS NETWORK
Connected
Generosity
Cascades
EXPERIMENTAL
NETWORK
Connected
How Do We Take Our Natural
Social Networks Online?
Connected
Connected
Online
Networks
Connected
FULL NETWORK
Online
Networks
Connected
NO EFFECT!
Online
Networks
REAL FRIENDS
Connected
K Lewis, J Kaufman, M Gonzalez, A Wimmer, and NA
Christakis, “Tastes, Ties, and Tim...
Online
Networks
REAL FRIENDS
Connected
PLUS FACEBOOK
K Lewis, J Kaufman, M Gonzalez, A Wimmer, and NA
Christakis, “Tastes,...
Photo
Tagging
FACEBOOK
Connected
Smiling
Clusters
FACEBOOK
NETWORK
Smilers
Non
Smilers
Connected
Obesity
Clusters
FACEBOOK
NETWORK
Connected
Viral
Voting
FACEBOOK
NETWORK
Connected
Viral
Voting
FACEBOOK
NETWORK
Connected
Viral
Voting
FACEBOOK
NETWORK
Connected
Direct Effect Indirect Effects
0
50k
100k
150k
200k
250k
300k
350k
IncreaseinValid...
Connected
Connected
Initially targeted High influence & high receptiveness
Second wave More receptive
Third wave Increasing acceptan...
Email Data at Healthways
-Each node represents an
employee
-Each line represents >100
emails transferred between
nodes
BMI Ranks and Obesity at Healthways
Red lines show bi-directional ties
Grey lines are directed ties
Body Mass Index (BMI) ...
Bikewalk Program in Blue Zones by Healthways
-Each node represents an
individual
-Green nodes are predicted
adopters for t...
Connected
Connected
Network
Connected
Theoretical Differences in Epidemic CurvesCUMULATIVEINCIDENCE
OFCONTAGION
DAILYINCIDENCE
OFCONTAGION
TIME TIME
Connected
Population
RANDOM PEOPLE
Connected
Population
PEOPLE &
FRIENDS
Connected
Observed Differences in Epidemic Curves
CUMULATIVEINCIDENCE
OFINFLUENZA
DAILYINCIDENCE
OFINFLUENZA
DAYS SINCE SE...
Connected
PATHOGENS INFORMATION NORMS BEHAVIORS
Contagious Outbreaks
Connected
Twitter Data!
2/3 of the Twittershpere
• 476,553,560 tweets
• 40,171,624 users
• 1,468,365,182 follows
June-Dece...
Connected
Sensor vs. control – specific examples
Connected
Global view of lead times
Connected
More Active AND More Diverse
ConnectedConnected
Early Warning, Even Out of Sample
Powerful
Friends
Connected
Friends as Data
Friends as Motivators
Friends as Multipliers
Friends as Sensors
Connected
Connected
Connected
Realize Your Own Network Power
Connected
Thank You!
James Fowler: The Power of Friends: Business Applications of Network Science
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James Fowler: The Power of Friends: Business Applications of Network Science

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James H. Fowler earned a PhD from Harvard in 2003 and is currently Professor of Medical Genetics and Political Science at the University of California, San Diego. His work lies at the intersection of the natural and social sciences, with a focus on social networks, behavior, evolution, politics, genetics, and big data.

James was was named one of Foreign Policy’s Top 100 Global Thinkers, TechCrunch’s Top 20 Most Innovative People in Democracy, and Most Original Thinker of the year by The McLaughlin Group. Together with Nicholas Christakis, James wrote a book on social networks for a general audience called Connected. Connected has been translated into twenty languages, named an Editor’s Choice by the New York Times Book Review, and featured in Wired, Oprah’s Reading Guide, Business Week’s Best Books of the Year, and a cover story in New York Times Magazine.

We were delighted to host James in skatepark Waalhalla for #projectwaalhalla Social Science for Startups. See our meet up group for more events: http://www.meetup.com/Project-Waalhalla-Social-science-for-Startups

Published in: Technology, Health & Medicine
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James Fowler: The Power of Friends: Business Applications of Network Science

  1. 1. http://www.wordle.net
  2. 2. Who Are Your Friends? Who do you discuss Important Matters with? Who do you spend your Free Time with? Connected
  3. 3. One Pair Connected
  4. 4. Connected Many Pairs
  5. 5. Connected Interconnected
  6. 6. Connected Social Network
  7. 7. The Power of Friends Connected Friends as Data Friends as Motivators Friends as Multipliers Friends as Sensors
  8. 8. The Framingham Heart Study Connected Original Cohort 1948 N = 5,209 Offspring Cohort 1971 N = 5,124 Gen 3 Cohort 2002 N ~ 4,000
  9. 9. Obesity Clusters FHS NETWORK Connected
  10. 10. Three Degrees Of Association FHS NETWORK Connected
  11. 11. HOMOPHILY Causes of Similarity and Clustering INFLUENCE CONTEXT Connected
  12. 12. The Spread Of Obesity Connected FROM 1971 TO 2003
  13. 13. Spread of Obesity Connected NA Christakis and JH Fowler, “The Spread of Obesity in a Large Social Network Over 32 Years,” New England Journal of Medicine 2007; 357: 370-379 Ego-Perceived Friend Mutual Friend Alter-Perceived Friend Same Sex Friend Opposite Sex Friend Spouse Sibling Same Sex Sibling Opposite Sex Sibling Immediate Neighbor Small Workplace Co-worker 0 100 200 300 PERCENTAGE INCREASE IN RISK OF OBESITY SOCIAL CONTACT
  14. 14. 20011971 Smoking Clusters FHS NETWORK Connected
  15. 15. Drinking Clusters FHS NETWORK Connected
  16. 16. ANGER HAPPINESS Reading Emotions Connected
  17. 17. Happiness Clusters FHS NETWORK Connected
  18. 18. Generosity Cascades EXPERIMENTAL NETWORK Connected
  19. 19. How Do We Take Our Natural Social Networks Online? Connected
  20. 20. Connected
  21. 21. Online Networks Connected FULL NETWORK
  22. 22. Online Networks Connected NO EFFECT!
  23. 23. Online Networks REAL FRIENDS Connected K Lewis, J Kaufman, M Gonzalez, A Wimmer, and NA Christakis, “Tastes, Ties, and Time,” Social Networks 2008; 30:
  24. 24. Online Networks REAL FRIENDS Connected PLUS FACEBOOK K Lewis, J Kaufman, M Gonzalez, A Wimmer, and NA Christakis, “Tastes, Ties, and Time,” Social Networks 2008; 30:
  25. 25. Photo Tagging FACEBOOK Connected
  26. 26. Smiling Clusters FACEBOOK NETWORK Smilers Non Smilers Connected
  27. 27. Obesity Clusters FACEBOOK NETWORK Connected
  28. 28. Viral Voting FACEBOOK NETWORK Connected
  29. 29. Viral Voting FACEBOOK NETWORK Connected
  30. 30. Viral Voting FACEBOOK NETWORK Connected Direct Effect Indirect Effects 0 50k 100k 150k 200k 250k 300k 350k IncreaseinValidatedVote Friends CloseFriends
  31. 31. Connected
  32. 32. Connected Initially targeted High influence & high receptiveness Second wave More receptive Third wave Increasing acceptance Measuring susceptibility-- Intervention is more effective Express Scripts
  33. 33. Email Data at Healthways -Each node represents an employee -Each line represents >100 emails transferred between nodes
  34. 34. BMI Ranks and Obesity at Healthways Red lines show bi-directional ties Grey lines are directed ties Body Mass Index (BMI) > 30 is considered obese
  35. 35. Bikewalk Program in Blue Zones by Healthways -Each node represents an individual -Green nodes are predicted adopters for the Bikewalk program
  36. 36. Connected
  37. 37. Connected Network
  38. 38. Connected Theoretical Differences in Epidemic CurvesCUMULATIVEINCIDENCE OFCONTAGION DAILYINCIDENCE OFCONTAGION TIME TIME
  39. 39. Connected Population RANDOM PEOPLE
  40. 40. Connected Population PEOPLE & FRIENDS
  41. 41. Connected Observed Differences in Epidemic Curves CUMULATIVEINCIDENCE OFINFLUENZA DAILYINCIDENCE OFINFLUENZA DAYS SINCE SEPTEMBER 1 DAYS SINCE SEPTEMBER 1 0 20 40 60 80 100 120 0.000.020.420.060.08 0.00000.00040.00080.0012 0 20 40 60 80 100 120
  42. 42. Connected PATHOGENS INFORMATION NORMS BEHAVIORS Contagious Outbreaks
  43. 43. Connected Twitter Data! 2/3 of the Twittershpere • 476,553,560 tweets • 40,171,624 users • 1,468,365,182 follows June-December 2009 Kwak, H., Lee, C., Park, H., & Moon, S. (2010). What is Twitter, a social network or a news media. Proceedings of the 19th international conference on World wide web, 591–600.  66,935,466 tweets using a hashtag  4,093,624 different hashtags  1,620,896 users using hashtags
  44. 44. Connected Sensor vs. control – specific examples
  45. 45. Connected Global view of lead times
  46. 46. Connected More Active AND More Diverse
  47. 47. ConnectedConnected Early Warning, Even Out of Sample
  48. 48. Powerful Friends Connected Friends as Data Friends as Motivators Friends as Multipliers Friends as Sensors
  49. 49. Connected
  50. 50. Connected
  51. 51. Connected Realize Your Own Network Power
  52. 52. Connected Thank You!

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