We study learning and influence in a setting where agents communicate according to an arbitrary social network and naively update their beliefs by repeatedly taking weighted averages of their neighbors' opinions. A focus is on conditions under which beliefs of all agents in large societies...

We examine how three different communication processes operating through social networks are affected by homophily - the tendency of individuals to associate with others similar to themselves. Homophily has no effect if messages are broadcast or sent via shortest paths; only connection density...

Homophily is the tendency of people to associate relatively more with those who are similar to them than with those who are not. In Golub and Jackson (2010a), we introduced degree-weighted homophily (DWH), a new measure of this phenomenon, and showed that it gives a lower bound on the time it...

We model contagions and cascades of failures among organizations linked through a network of financial interdependencies. We identify how the network propagates discontinuous changes in asset values triggered by failures (e.g., bankruptcies, defaults, and other insolvencies) and use that to...

Previous allocation rules for network games, such as the Myerson Value, implicitly or explicitly take the network structure as fixed. In many situations, however, the network structure can be altered by players. This means that the value of alternative network structures (not just sub-networks)...

We study countries choosing armament levels and then whether or not to go to war. We show that if the costs of war are not overly high or low, then all equilibria must involve "dove," "hawk," and "deterrent" strategies and the probability of war is positive (but less than one) in any given...

We introduce a model in which agents observe signals about the state of the world, and some signals are open to interpretation. Our decision makers first interpret each signal based on their current belief and then form a posterior on the sequence of interpreted signals. This ‘double...

We define a general class of network formation models, Statistical Exponential Random Graph Models (SERGMs), that nest standard exponential random graph models (ERGMs) as a special case. We provide the first general results on when these models' (including ERGMs) parameters estimated from the...

We provide an overview and synthesis of the literatures analyzing games in which players are connected via a network structure. We discuss, in particular, the impact of the structure of the network on individuals' behaviors. We focus on game theoretic modeling, but also include some discussion...