Gossip: Identifying Central Individuals in a Social Network

Abstract

Is it possible, simply by asking a few members of a community, to identify individuals who are best placed to diffuse information? A simple model of shows how boundedly rational individuals can, just by tracking gossip about people, identify those who are most central in a network according to diffusion (a measure of network centrality which nests existing ones, and predicts the extent to which piece of information seeded to a network member diffuses in finite time). Using rich network data from 35 Indian villages, we find that respondents accurately nominate those who are central -- not just traditional leaders or those with many friends. In a subsequent randomized field experiment in 213 villages, we track the of a piece of information initially given to a small number of in each community. Seeds who are nominated by others lead to a near tripling of the spread of information relative to randomly chosen seeds. Diffusion centrality accounts for some, but not all, of the extra from these nominated seeds compared to other seeds (including those with high social status) in our experiment.