  In this work we introduce a new model of decision-making by agents in a
social network. Agents have innate preferences over the strategies but, because
of the social interactions, the decision of the agents are not only affected by
their innate preferences but also by the decision taken by their social
neighbors. We assume that the strategies of the agents are embedded in an
{approximate} metric space. Furthermore, departing from the previous
literature, we assume that, due to the lack of information, each agent locally
represents the trend of the network through an aggregate value, which can be
interpreted as the output of an aggregation function. We answer some
fundamental questions related to the existence and efficiency of pure Nash
equilibria.
