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Gossip: Identifying Central Individuals in a Social Network / Abhijit Banerjee, Arun G. Chandrasekhar, Esther Duflo, Matthew O. Jackson.

NBER Working papers Available online

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Format:
Book
Author/Creator:
Banerjee, Abhijit.
Contributor:
National Bureau of Economic Research.
Chandrasekhar, Arun G.
Duflo, Esther.
Jackson, Matthew O.
Series:
Working Paper Series (National Bureau of Economic Research) no. w20422.
NBER working paper series no. w20422
Language:
English
Physical Description:
1 online resource: illustrations (black and white);
Other Title:
Gossip
Place of Publication:
Cambridge, Mass. National Bureau of Economic Research 2014.
Summary:
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.
Notes:
Print version record
August 2014.

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