Wireless network operators increasingly deploy WiFi hotspots and low-power, low-range base stations in order to satisfy users' growing demands for context-aware services and performance. In addition to providing better service, such capillary infrastructure deployment threatens users' privacy with respect to their social ties and communities, as it allows infrastructure owners to infer users' daily social encounters with increasing accuracy, much to the detriment of their privacy. Yet, to date, there are no evaluations of the privacy of communities in pervasive wireless networks. In this paper, we address the important issue of privacy in pervasive communities by experimentally evaluating the accuracy of an adversary-owned set of wireless sniffing stations in reconstructing the communities of mobile users. During a four-month trial, 80 participants carried mobile devices and were eavesdropped on by an adversarial wireless mesh network on a university campus. To the best of our knowledge, this is the first study that focuses on the privacy of communities in a deployed pervasive network and provides important empirical evidence on the accuracy and feasibility of community tracking in such networks.