Gossip: Identifying Central Individuals in a Social Network GOSSIP: IDENTIFYING CENTRAL INDIVIDUALS IN A SOCIAL NETWORK

Is it possible, simply by asking a few members of a community, to identify individuals who are best placed to diffuse information? A model of diffusion shows how members of a community can, just by tracking gossip about others, identify those who are most central in a network according to “diffusion centrality” – a network centrality measure that predicts the diffusion of a piece of information seeded with a network member. Using rich network data from 33 Indian villages, we find that villagers accurately nominate those who are diffusion central – not just those with many friends or in powerful positions. Via a randomized field experiment design to test this theory, in 212 villages we track the diffusion of a piece of information initially given to a small number of “seeds” in each community. Relative to random seeds, seeds nominated by villagers as good “gossips” lead to a 66% increase in the spread of information (from a low basis). The success of the nominees is partly, but not entirely, accounted for by their diffusion centrality. JEL Classification Codes: D85, D13, L14, O12, Z13