Working Paper: CEPR ID: DP10120
Authors: 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 in- dividuals? 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.
Keywords: centrality; diffusion; gossip; influence; networks; social learning
JEL Codes: D13; D85; L14; O12; Z13
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| gossip (Y60) | individuals' ability to assess centrality (D80) |
| mentions of individuals in gossip (Z13) | nominations for information diffusion (O33) |
| nominations for information diffusion (O33) | diffusion centrality (R12) |
| gossip (Y60) | accurate identification of individuals with high diffusion centrality (D85) |