Example: Viral Propagation
Example: Viral Propagation 6
Example: Viral Marketing a Recommendation referral program a Senders and followers of recommendations receive discounts on products 1o% credit 10% off
Example: Viral Marketing Recommendation referral program: Senders and followers of recommendations receive discounts on products 7
Early Empirical Studies of Diffusion and Influence 8 a Sociological study of diffusion of innovation a Spread of new agricultural practices[Ryan-Gross 1943 Studied the adoption of a new hybrid -corn between the 259 farmers in lowa Found that interpersonal network plays important role a Spread of new medical practices [Coleman et al 1966 Studied the adoption of new drug between doctors in lllinois Clinical studies and scientific evaluation were not sufficient to convince doctors It was the social power of peers that led to adoption n The contagion of obesity [Christakis et al. 2007 a If you have an overweight friend, your chance of becoming obese by57%! increase by
Early Empirical Studies of Diffusion and Influence Sociological study of diffusion of innovation: Spread of new agricultural practices[Ryan-Gross 1943] ◼ Studied the adoption of a new hybrid-corn between the 259 farmers in Iowa ◼ Found that interpersonal network plays important role Spread of new medical practices [Coleman et al 1966] ◼ Studied the adoption of new drug between doctors in Illinois ◼ Clinical studies and scientific evaluation were not sufficient to convince doctors ◼ It was the social power of peers that led to adoption The contagion of obesity [Christakis et al. 2007] If you have an overweight friend, your chance of becoming obese increase by 57%! 8
Applications of social Influence Models 9 Backward network Forward network engineering engineering Backward Learn from Forward predictions observed data predictions a Forward Predictions: viral marketing influence maximization a Backward Predictions: effector/initiator finding, sensor placement cascade detection
Applications of Social Influence Models Forward Predictions: viral marketing, influence maximization Backward Predictions: effector/initiator finding, sensor placement, cascade detection Forward network engineering Backward predictions Forward predictions Backward network engineering Learn from observed data 9
Dynamics of Viral Marketing (Leskovec 07) Senders and followers of recommendations receive discounts on prodUCtS 10% credit it 10%of Recommendations are made to any number of people at the time of purchase Only the recipient who buys first gets a discount
10 Dynamics of Viral Marketing (Leskovec 07) Senders and followers of recommendations receive discounts on products 10% credit 10% off ◼ Recommendations are made to any number of people at the time of purchase ◼ Only the recipient who buys first gets a discount 10