Social network-embedded prediction markets: The effects of information acquisition and communication on predictions

Authors:
Liangfei Qiu;Huaxia Rui;Andrew Whinston
Affiliations:
Department of Economics, University of Texas at Austin, Austin, TX 78712, USA;Simon School of Business, University of Rochester, Rochester, NY 14627, USA;McCombs School of Business, University of Texas at Austin, Austin, TX 78712, USA
Venue:
Decision Support Systems
Year:
2013

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Abstract

Information aggregation mechanisms are designed explicitly for collecting and aggregating dispersed information. An excellent example of the use of this ''wisdom of crowds'' is a prediction market. The purpose of our social network-embedded prediction market is to suggest that carefully designed market mechanisms can elicit and gather dispersed information that can improve our predictions. Simulation results show that our network-embedded prediction market can produce better predictions as a result of the information exchange in social networks and can outperform other non-networked prediction markets. It is shown that forecasting errors decrease with the cost of acquiring information in a network-embedded prediction market. We also develop an information system that combines the power of prediction markets with the popularity of Twitter.