Social Learning Applications in Resource Constrained Networks

Efficient design of social networking applications must take account of two guiding principles: the adaptive processes by which humans learn and spread new information, and the communication and technological constraints that in turn define the boundaries of human social behavior in virtual communities. In this paper, we introduce the concept of social learning in decentralized, resource-constrained networks. We present a mathematical model for spread of information and derive the optimum strategy that minimizes the total cost of learning in cooperative social networks. We then extend our model to allow individuals to limit their cooperative behavior in spreading their knowledge. Our results demonstrate that increased cooperation reduces the overall cost and accelerates the rate of learning new information.