Gossip: Identifying Central Individuals in a Social Network
Published By: BREAD | Published Date: June, 01 , 2014The paper examines individuals’ abilities to identify the highly central people in their social networks, where centrality is defined by diffusion centrality (Banerjee, Chandrasekhar, Duflo, and Jackson, 2013), which characterizes a node’s influence in spreading information. It first show that diffusion centrality nests standard centrality measures – degree, eigenvector and Katz-Bonacich centrality – as extreme special cases. Next, it shows that boundedly rational individuals can, simply by tracking sources of gossip, identify who is central in their social network in the specific sense of having high diffusion centrality.
Author(s): Abhijit Banerjee, Arun G Chandrasekhar, Esther Duflo, Mathew O. Jackson | Posted on: Jun 19, 2014 | Views(838) | Download (1166)