Potential networks, contagious communities, and understanding social network structure

In this paper we provide evidence that digital social networks look fundamentally different from social networks. We show that online social networks look like a contagion spread over traditional models for social networks. Thus, if these tradi-tional models are correct, then digital social networks and social networks differ in key properties, and we will need different models to describe each. This also indicates that using data from digital social networks may mislead us if we try to use it to directly infer the structure of social networks. Additionally, we describe a framework that we call “poten-tial networks ” that may help to use information from digital networks to infer the structure of social networks. Poten-tial networks is a two phase model of social networks. The first phase is the“potential”network. However, this network may not be directly observed and might not even exist an any normal manner. A random process is run over a po-tential network to produce a behavioral network, the second phase, which can be observed. We then discuss applications of this two-phase framework