Comments on: Book Review: The Stag Hunt and the Evolution of Social Structure http://emergentchaos.com/archives/2006/02/book-review-the-stag-hunt-and-the-evolution-of-social-structure.html The Emergent Chaos Jazz Combo Mon, 15 Mar 2010 15:02:09 +0000 http://wordpress.org/?v=2.9.2 hourly 1 By: Allan Friedman http://emergentchaos.com/archives/2006/02/book-review-the-stag-hunt-and-the-evolution-of-social-structure.html/comment-page-1#comment-1917 Allan Friedman Thu, 23 Feb 2006 10:17:28 +0000 http://emergentchaos.com/?p=1513#comment-1917 Chris, thanks for the review of what sounds like a delightfully polymath book. I may have to pick up a copy for the next long flight. *shameless plug* If anyone out there is interested in the questions of individual and group incentives with respect to network structure and attributes, I'll be presenting a paper at the Sunbelt Social Network Conference on "The Tragedy of the Network", and I can email a draft to anyone interested. <blockquote> <u>The Tragedy of the Network</u><br> In many social contexts, individuals choose a set of social interactions to maximize their private benefit, but the resulting social network structure is a public phenomenon that can affect all members of the network. Previous research (Lazer and Friedman 2005) has found that more efficient collaborative networks (e.g. small world networks) yield poor system-wide results. In this paper, using agent-based modeling and evolutionary algorithms, we take the efficiency of the network as endogenous to the system of problem-solvers, assuming that individuals choose a set of social interactions to maximize their private benefit. We then focus on the social success of actors in the resulting structure. Results show that while sparse networks perform better in the long run, individual actors will create a well-connected network through which information will flow rapidly, resulting in a poorly performing system. The "tragedy of the network" is that if everyone acts in their best interest, the resulting network will be worse for everyone. We discuss several examples of this stylized model from a variety of disciplines. </br></blockquote> Earlier related work here: <a href="http://papers.ssrn.com/sol3/papers.cfm?abstract_id=832627" rel="nofollow"><a href="http://papers.ssrn.com/sol3/papers.cfm?abstract_id=832627" rel="nofollow">http://papers.ssrn.com/sol3/papers.cfm?abstract_id=832627</a></a> Chris, thanks for the review of what sounds like a delightfully polymath book. I may have to pick up a copy for the next long flight.
*shameless plug*
If anyone out there is interested in the questions of individual and group incentives with respect to network structure and attributes, I’ll be presenting a paper at the Sunbelt Social Network Conference on “The Tragedy of the Network”, and I can email a draft to anyone interested.

The Tragedy of the Network
In many social contexts, individuals choose a set of social interactions to maximize their private benefit, but the resulting social network structure is a public phenomenon that can affect all members of the network. Previous research (Lazer and Friedman 2005) has found that more efficient collaborative networks (e.g. small world networks) yield poor system-wide results. In this paper, using agent-based modeling and evolutionary algorithms, we take the efficiency of the network as endogenous to the system of problem-solvers, assuming that individuals choose a set of social interactions to maximize their private benefit. We then focus on the social success of actors in the resulting structure. Results show that while sparse networks perform better in the long run, individual actors will create a well-connected network through which information will flow rapidly, resulting in a poorly performing system. The “tragedy of the network” is that if everyone acts in their best interest, the resulting network will be worse for everyone. We discuss several examples of this stylized model from a variety of disciplines.

Earlier related work here:
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=832627

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