G2TT
来源类型Discussion paper
规范类型论文
来源IDDP10120
DP10120 Gossip: Identifying Central Individuals in a Social Network
Abhijit Banerjee; Matthew O. Jackson; Esther Duflo; Arun G. Chandrasekhar
发表日期2014-08-31
出版年2014
语种英语
摘要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.
主题Development Economics
关键词Centrality Diffusion Gossip Influence Networks Social learning
URLhttps://cepr.org/publications/dp10120
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/538953
推荐引用方式
GB/T 7714
Abhijit Banerjee,Matthew O. Jackson,Esther Duflo,et al. DP10120 Gossip: Identifying Central Individuals in a Social Network. 2014.
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