BSF:2014389: Networked Markets

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In recent years, online social networks have emerged as an important medium for communication, and as a result can provide an effective platform for markets. Due to the scale and complexity of social networking applications, markets in these environments require a different theory than the theory which guides the design of traditional internet markets. This project aims to study markets that operate in networked environments. The goal of this research is to develop both theory and empirical methods that are suitable for networked market design. This research has three major thrusts. The first goal is to study incentives in network cascades. Information cascades spread information in networks and incentivizing individuals to spread large cascades is a central problem for network market design. The second objective is to study competition in networked markets. In some cases, cascades are initiated by competing agencies that seek to influence individuals to adopt the technology or idea they promote. More generally, competition in networks spurs complex dynamics that are challenging to analyze. This project analyzes equilibrium of such interactions, as well as principles of market design in these complex environments. The third thrust develops data mining techniques to study the economics of social marketing platforms. The main challenge in such markets is that the social networking services do not control the content being published, and users often post advertisements without any indication. This makes analysis of social marketing platforms a challenging data mining problem of detecting covert advertisements. These methods for analysis and design of networked markets could have a significant impact on internet economics.