http://www.wordle.net

Who Are Your Friends?

Who do you discuss Important Matters with?

Who do you spend your Free Time with?

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One Pair

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Many Pairs

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Interconnected

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Social Network

The Power of FriendsConnected

Friends as DataFriends as MotivatorsFriends as Multipliers

Friends as Sensors

The Framingham Heart Study

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Original Cohort1948N = 5,209

Offspring Cohort1971N = 5,124

Gen 3 Cohort2002N ~ 4,000

ObesityClusters

FHS NETWORK

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Three DegreesOf Association

FHS NETWORK

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HOMOPHILY

Causes of Similarity and Clustering

INFLUENCE CONTEXT

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The SpreadOf Obesity

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FROM 1971 TO 2003

Spread of Obesity

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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

20011971

Smoking ClustersFHS NETWORK

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Drinking ClustersFHS NETWORK

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ANGER HAPPINESS

Reading Emotions

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HappinessClusters

FHS NETWORK

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GenerosityCascades

EXPERIMENTALNETWORK

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How Do We Take Our Natural Social Networks Online?

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OnlineNetworks

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FULL NETWORK

OnlineNetworks

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NO EFFECT!

OnlineNetworks

REAL FRIENDS

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K Lewis, J Kaufman, M Gonzalez, A Wimmer, and NA Christakis, “Tastes, Ties, and Time,” Social Networks 2008; 30: 330-342

OnlineNetworks

REAL FRIENDS

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PLUS FACEBOOK

K Lewis, J Kaufman, M Gonzalez, A Wimmer, and NA Christakis, “Tastes, Ties, and Time,” Social Networks 2008; 30: 330-342

PhotoTagging

FACEBOOK

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SmilingClusters

FACEBOOK NETWORK

Smilers

NonSmilers

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ObesityClusters

FACEBOOK NETWORK

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ViralVoting

FACEBOOK NETWORK

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ViralVoting

FACEBOOK NETWORK

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ViralVoting

FACEBOOK NETWORK

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Initially targeted High influence & high receptivenessSecond wave More receptiveThird wave Increasing acceptance

Measuring susceptibility--Intervention is more effective

Express Scripts

Email Data at Healthways-Each node represents an employee -Each line represents >100 emails transferred between nodes

BMI Ranks and Obesity at HealthwaysRed lines show bi-directional ties

Grey lines are directed ties

Body Mass Index (BMI) > 30is considered obese

Bikewalk Program in Blue Zones by Healthways-Each node represents an individual-Green nodes are predicted adopters for the Bikewalk program

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Network

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Theoretical Differences in Epidemic CurvesC

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TIME TIME

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PopulationRANDOM PEOPLE

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PopulationPEOPLE & FRIENDS

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Observed Differences in Epidemic CurvesC

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DAYS SINCE SEPTEMBER 1 DAYS SINCE SEPTEMBER 1

0 20 40 60 80 100 120

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0.42

0.06

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0.00

080.

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PATHOGENS INFORMATION NORMS BEHAVIORS

Contagious Outbreaks

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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

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Sensor vs. control – specific examples

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Global view of lead times

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More Active AND More Diverse

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Early Warning, Even Out of Sample

PowerfulFriends

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Friends as DataFriends as MotivatorsFriends as MultipliersFriends as Sensors

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Realize Your Own Network Power

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Thank You!