Information Acquisition and Exchange in Social Networks

Abstract

This paper develops a framework for the analysis of information acquisition and exchange in social networks. In the static model, there is a symmetric Bayes-Nash Equilibrium where all players use a simple cut-off strategy involving the threshold degree. The inefficiency of information acquisition is caused by free-riding. In the dynamics of information exchange, there is a trade-off between taking immediate action and waiting: A player could wait to receive more information from her second-order neighbors, but the future is discounted. All else being equal, an earlier submission is preferred to a later one. A network-embedded prediction market is an appropriate application of the information network model. Using a variety of simulations of player trading, I show that as the cost of acquiring information decreases, so do the forecasting errors. The implication is similar to the efficient market hypothesis. As more and more players acquire information, the prediction market prices fully incorporate all available information, and thus yield better forecasts.