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Published August 2005 | Published
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The Economics of Social Networks


The science of social networks is a central field of sociological study, a major application of random graph theory, and an emerging area of study by economists, statistical physicists and computer scientists. While these literatures are (slowly) becoming aware of each other, and on occasion drawing from one another, they are still largely distinct in their methods, interests, and goals. Here, my aim is to provide some perspective on the research from these literatures, with a focus on the formal modeling of social networks and the two major types of models: those based on random graphs and those based on game theoretic reasoning. I highlight some of the strengths, weaknesses, and potential synergies between these two network modeling approaches.

Additional Information

I thank the Lee Center for Advanced Networking for financial support. I am very grateful to collaborators on networks projects, who have helped me learn about social networks and the fascinating questions they present; and who are inexorably tied to the views I take herein. So I thank (in chronological order), Asher Wolinsky, Alison Watts, Bhaskar Dutta, Anne van den Nouweland, Toni Calvó-Armengol, Francis Bloch, Gary Charness, Alan Kirman, Jernej Copic, Brian Rogers, Dunia Lopez-Pintado, and Leeat Yariv. I also thank Yann Bramoullé, Toni Calvó-Armengol, Yannis Ioannides, Alan Kirman, Dunia Lopez-Pintado, Laurent Mathevet, Nicolas Quérou, Alesssandro Vespignani, Stanley Wasserman, Duncan Watts, and Leeat Yariv for comments on an earlier draft. I am grateful to Tom Palfrey for an insightful discussion of the paper. This is a written version of a lecture prepared for presentation at the 2005 World Congress of the Econometric Society, which is to appear in the Proceedings of the 9th World Congress of the Econometric Society, edited by Richard Blundell, Whitney Newey, and Torsten Persson, Cambridge University Press.

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