#05-08
Behavioral Aspects of Learning in Social Networks:An Experimental Study
Syngjoo Choi, Douglas Gale and Shachar Kariv
Abstract: Networks are natural tools for understanding social and economic phenomena.
For example, all markets are characterized by agents connected
by complex, multilateral information networks, and the network structure
influences economic outcomes. In an earlier study, we undertook an experimental
investigation of learning in various three-person networks, each of
which gives rise to its own learning patterns. In the laboratory, learning
in networks is challenging and the difficulty of solving the decision problem
is sometimes massive even in the case of three persons. We found
that the theory can account surprisingly well for the behavior observed in
the laboratory. The aim of the present paper is to investigate important
and interesting questions about individual and group behavior, including
comparisons across networks and information treatments. We find that in
order to explain subjects’ behavior, it is necessary to take into account the
details of the network architecture as well as the information structure.
We also identify some “black spots” where the theory does least well in
interpreting the data.
Keywords:
JEL classifications : D82, D83, C92
