We study a sequential-learning model featuring a network of naive agents with Gaussian information structures. Agents …' actions in terms of network paths and use this formula to characterize the set of networks where naive agents eventually learn … expected welfare losses, across network structures. The probability of mislearning increases when link densities are higher and …

multiplex network who deal with coordination issues using social learning and payoff-driven dynamics. Agents form their …

been covered entirely by previous diffusion models: the network character of knowledge, compatibility of new knowledge with … already existing knowledge, and the fact that transmission of knowledge requires some form of attention. We employ a network …-of-networks approach, where agents are located within an innovation network and each agent itself contains another network composed of …

also discuss some of the more prominent models of network interactions, including recent advances regarding interdependent …

, learning and diffusion, and network games. I also include some background on social network characteristics and measurements …, models of network formation, models for the statistical analysis of social networks, as well as community detection. …