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Re: Social Capital
From: |
Catherine Dibble |
Subject: |
Re: Social Capital |
Date: |
Mon, 02 Jul 2001 16:30:09 -0400 |
hi Claudia,
Yes, there is a particularly interesting paper on this topic by
Troy Tassier and Filippo Menczer at the U of Iowa. They
addressed job markets, but their agent-based model of
social network formation has much broader and very interesting
implications for social capital in general and for related policies.
Leigh Tesfatsion's page of Network Researchers has a link to
Menczer's research site.
If it has not just appeared, this paper should be forthcoming soon
in the _IEEE Transactions on Evolutionary Computation_. Here
is its abstract:
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"Evolving Referral Networks in the Job Market"
by Troy Tassier (U of Iowa) and Filippo Menczer (U of Iowa)
ABSTRACT: We model a labor market that includes referral
networks using an agent-based simulation. Agents maximize their
employment satisfaction by allocating resources to build friendship
networks and by adjusting search intensity. We use a local-selection
evolutionary algorithm, which maintains a diverse population of
strategies, to study the adaptive graph topologies resulting from
the model. The evolved networks display mixtures of regularity and
randomness, as in small-world networks. A second characteristic
emerges in our model as time progresses: the population loses
efficiency due to over-competition for job referral contacts in a
way similar to social dilemmas such as the tragedy of the commons.
Analysis reveals that the loss of global fitness is driven by an
increase in individual robustness, which allows agents to live
longer by surviving job losses. The behavior of our model suggests
predictions for a number of policies.
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Best regards,
Catherine
*============================================*
Never doubt that a small group of thoughtful, committed
citizens can change the world. -- Margaret Mead
Catherine Dibble address@hidden
Department of Geography www.glue.umd.edu/~cdibble
2181 LeFrak Hall
University of Maryland
College Park, MD 20742 FAX: 01 301 314 9299
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