Gossip: Identifying Central Individuals in a Social Network
نویسندگان
چکیده
Can we identify the members of a community who are bestplaced 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. JEL Classification Codes: D85, D13, L14, O12, Z13
منابع مشابه
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...
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عنوان ژورنال:
- CoRR
دوره abs/1406.2293 شماره
صفحات -
تاریخ انتشار 2014