Communication and Learning in Social Networks

Most individuals form their opinions about the quality of products, social trends and political issues via their interactions in social and economic networks. While the role of social networks as a conduit for information is as old as humanity, recent social and technological developments, such as Facebook, Blogs and Twitter, have added further to the complexity of network interactions. Despite the ubiquity of social networks and their importance in communication, we know relatively little about how opinions form and information is transmitted in such networks. For example, does a large social network of individuals holding disperse information aggregate it efficiently? What kinds of communication structures are likely to emerge?

Motivated by the above considerations, Kostas Bimpikis and Professor Asu Ozdaglar, in collaboration with Professor Daron Acemoglu from the MIT Economics department, developed a framework for the analysis of dynamic strategic interactions over complex networks. Their approach relies on using game-theoretic models that study the costly link formation decisions of agents and their subsequent information exchange on the resulting communication networks. This work provides a complete characterization of communication cost structures and networks under which information can be efficiently aggregated in strategic environments. This research lies at the intersection of economics, operations research, and network science and, as such, requires tools from game theory, applied probability and optimization.