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Gossip: Identifying Central Individuals in a Social Network

Author

Listed:
  • Abhijit Banerjee
  • Arun G. Chandrasekhar
  • Esther Duflo
  • Matthew O. Jackson
Abstract
Can we identify the members of a community who are best- placed to diffuse information simply by asking a random sample of individuals? We show that boundedly-rational individuals can, simply by tracking sources of gossip, identify those who are most central in a network according to "diffusion centrality," which nests other standard centrality measures. Testing this prediction with data from 35 Indian villages, we find that respondents accurately nominate those who are diffusion central (not just those with many friends). Moreover, these nominees are more central in the network than traditional village leaders and geographically central individuals.

Suggested Citation

  • Abhijit Banerjee & Arun G. Chandrasekhar & Esther Duflo & Matthew O. Jackson, 2014. "Gossip: Identifying Central Individuals in a Social Network," NBER Working Papers 20422, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:20422
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    JEL classification:

    • D13 - Microeconomics - - Household Behavior - - - Household Production and Intrahouse Allocation
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification

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