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.
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Paper provided by California Institute of Technology, Division of the Humanities and Social Sciences in its series Working Papers with number
1237.
Length: 86 pages Date of creation: Aug 2005 Date of revision: Publication status: Published in Advances in Economics & Econometrics, Theory & Applications: Ninth World Congress of the Econometric Society, ed. by Richard Blundell, Whitney Newey, and Torsten Persson. Cambridge University Press, 2006, Chap. 1, Vol. 1, pg. 1-56. Handle: RePEc:clt:sswopa:1237
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