Social Learning in Social Networks
This paper analyzes a model of social learning in a social network. Agents decide whether or not to adopt a new technology with unknown payoffs based on their prior beliefs and the experiences of their neighbors in the network. Using a mean-field approximation, I prove that the diffusion process alw...
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| Format: | Working Paper |
| Language: | en_US |
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Cambridge, MA; Alfred P. Sloan School of Management, Massachusetts Institute of Technology
2011
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| Online Access: | http://hdl.handle.net/1721.1/66569 |
| _version_ | 1826204986516701184 |
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| author | Lamberson, PJ |
| author_facet | Lamberson, PJ |
| author_sort | Lamberson, PJ |
| collection | MIT |
| description | This paper analyzes a model of social learning in a social network. Agents decide whether or not to adopt a new technology with unknown payoffs based on their prior beliefs and the experiences of their neighbors in the network. Using a mean-field approximation, I prove that the diffusion process always has at least one stable equilibrium, and I examine the dependence of the set of equilibria on the model parameters and the structure of the network. In particular, I show how first and second order stochastic dominance shifts in the degree distribution of the network impact diffusion. I find that the relationship between equilibrium diffusion levels and network structure depends on the distribution of payoffs to adoption and the distribution of agents' prior beliefs regarding those payoffs, and I derive the precise conditions characterizing those relationships. |
| first_indexed | 2024-09-23T13:05:17Z |
| format | Working Paper |
| id | mit-1721.1/66569 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:05:17Z |
| publishDate | 2011 |
| publisher | Cambridge, MA; Alfred P. Sloan School of Management, Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/665692019-04-10T12:27:20Z Social Learning in Social Networks Lamberson, PJ social networks diffusion mean-field analysis stochastic dominance This paper analyzes a model of social learning in a social network. Agents decide whether or not to adopt a new technology with unknown payoffs based on their prior beliefs and the experiences of their neighbors in the network. Using a mean-field approximation, I prove that the diffusion process always has at least one stable equilibrium, and I examine the dependence of the set of equilibria on the model parameters and the structure of the network. In particular, I show how first and second order stochastic dominance shifts in the degree distribution of the network impact diffusion. I find that the relationship between equilibrium diffusion levels and network structure depends on the distribution of payoffs to adoption and the distribution of agents' prior beliefs regarding those payoffs, and I derive the precise conditions characterizing those relationships. 2011-10-24T21:08:16Z 2011-10-24T21:08:16Z 2009-10 Working Paper http://hdl.handle.net/1721.1/66569 en_US MIT Sloan School of Management Working Paper;4763-09 application/pdf Cambridge, MA; Alfred P. Sloan School of Management, Massachusetts Institute of Technology |
| spellingShingle | social networks diffusion mean-field analysis stochastic dominance Lamberson, PJ Social Learning in Social Networks |
| title | Social Learning in Social Networks |
| title_full | Social Learning in Social Networks |
| title_fullStr | Social Learning in Social Networks |
| title_full_unstemmed | Social Learning in Social Networks |
| title_short | Social Learning in Social Networks |
| title_sort | social learning in social networks |
| topic | social networks diffusion mean-field analysis stochastic dominance |
| url | http://hdl.handle.net/1721.1/66569 |
| work_keys_str_mv | AT lambersonpj sociallearninginsocialnetworks |