Published September 2015
| Version Published + Supplemental Material + Submitted
Journal Article
Open
Strategic Learning and the Topology of Social Networks
Creators
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1.
University of Pennsylvania
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2.
University of California, Berkeley
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3.
California Institute of Technology
Abstract
We consider a group of strategic agents who must each repeatedly take one of two possible actions. They learn which of the two actions is preferable from initial private signals and by observing the actions of their neighbors in a social network.
Additional Information
© 2015 The Econometric Society. Manuscript received November, 2013; final revision received May, 2015. We would like to thank Shahar Kariv for introducing us to this field. For commenting on drafts of this paper, we would like to thank Nageeb Ali, Ben Golub, Eva Lyubich, Markus Mobius, Ariel Rubinstein, Ran Shorrer, Glen Weyl, and, especially, Scott Kominers. The work of Mossel is supported by NSF award DMS 1106999, by ONR award N000141110140, and by ISF Grant 1300/08. The work of Sly is supported by a Sloan Research Fellowship in mathematics and by NSF award DMS 1208339. The research of Tamuz was supported in part by a Google Europe Fellowship.Attached Files
Published - Mossel_et_al-2015-Econometrica.pdf
Submitted - 1209.5527.pdf
Supplemental Material - ecta1540-sup-0001-Supplement.pdf
Files
1209.5527.pdf
Additional details
Identifiers
- Eprint ID
- 61718
- Resolver ID
- CaltechAUTHORS:20151029-144956303
Related works
- Describes
- https://arxiv.org/abs/1209.5527 (URL)
Funding
- NSF
- DMS 1106999
- Office of Naval Research (ONR)
- N000141110140
- NSF
- 1300/08
- Alfred P. Sloan Foundation
- NSF
- DMS 1208339
Dates
- Created
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2015-10-29Created from EPrint's datestamp field
- Updated
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2021-11-10Created from EPrint's last_modified field
Caltech Custom Metadata
- Caltech groups
- Mathematics Department