Abstract
Various social networks share prominent features: clustering, rightskewed degree distribution, segregation into densely connected com- munities. We build network formation game rationalizing these features with signal-extraction benet by network participants. The players build network to exchange their private signals on the relevant state. We show that a family of Nash equilibrium networks possesses the above-mentioned prominent features of real networks. We show, furthermore, that networks with these features are e¢ cient.
Keywords
network formation, endogenous information benet, clustering, hubs, differentiated priors, Bayesian learning in networks.;
JEL codes
- D82: Asymmetric and Private Information • Mechanism Design
- D85: Network Formation and Analysis: Theory
- C72: Noncooperative Games
Reference
Thibault Laurent, and Elena Panova, “Clustering in communication networks with di¤erent-minded participants”, TSE Working Paper, n. 20-1147, September 2020, revised August 2022.
See also
Published in
TSE Working Paper, n. 20-1147, September 2020, revised August 2022