We propose a random network model incorporating heterogeneity of agents and a continuous notion of homophily. Unlike … the vast majority of the corresponding economic literature, we capture homophily in terms of similarity rather than … equality of agents. We show that if links between similar agents are indeed more likely, our homophilous random network model …

We propose a random network model incorporating heterogeneity of agents and a continuous notion of homophily. Unlike … the vast majority of the corresponding economic literature, we capture homophily in terms of similarity rather than … equality of agents. We show that if links between similar agents are indeed more likely, our homophilous random network model …

We propose a random network model incorporating heterogeneity of agents and a continuous notion of homophily. Unlike … positive level of homophily our model exhibits clustering, that is an increased probability of linkage given a common neighbor … the vast majority of the corresponding economic literature, we capture homophily in terms of similarity rather than …

payoffs depend on the social distance between them. We characterize the clustering coefficient and average path length in … distributions, positive assortativity of degrees, and clustering-degree correlation. …

equilibrium outcomes on network clustering — the probability that two individuals with a mutual neighbor are connected to each … spread. Previously developed frameworks capture local social influence using network games, but discard local correlation in … players' strategies. This paper develops a network games framework that allows for local correlation in players' strategies by …

We develop a dynamic network formation model that can explain the observed nestedness in real-world networks. Links are … identify the networks to which the network formation process converges and find that they are nested split graphs. We … by real-world networks. Using four different network datasets, we empirically test our model and show that it fits well …

that amount. The information that the nodes receive through the network is the revenue from investments in links. We prove … maximizing the aggregate profit, are still the all-encompassing star and the complete network, with the sole and rare exception … of a highly particular case where there is a draw between the allencompassing star, the complete network and a whole …

The communities in a network have distinct characteristics and interrelationships. Community discovery methods based on … node embedding and deep learning have surpassed spectral clustering and statistical inference as the preferred methods for … handling high-dimensional network data. Community detection in graph networks using graph neural networks (GNNs) is a rapidly …

methodological tools assessing network characteristics at the dyadic level are lacking for aggregated networks (such as the network … knowledge flows. To do so we first define a new measure to assess 'network proximity' at the level of the regional dyad, based … European countries (France, Germany, Italy, Spain, the United Kingdom). The studied network is then composed of all the …

networks, such coordination may be very difficult to achieve and may depend on the communication technology and the network … structure. We examine how pre-play communication and clustering within networks affect coordination in a challenging … credibility and show, both theoretically and experimentally, an interaction effect of network structure and communication …