Social Network Analysis has often focused on the structure of the network without taking into account the char- acteristics of the individual involved. In this work, we aim at identifying how individual differences in psychological traits affect the community structure of social networks. Instead of choosing to study only either structural or psychological properties of an individul, our aim is to exhibit in which way the psychological attributes of interacting individuals impacts the social network topology. Using psychological data from the myPersonality application and social data from Facebook, we confront the personality traits of the subjects to metrics obtained after applying the C3 community detection algorithm to the social neighborhood of the subjects. We observe that introverts tend to have less communities and hide into large communities, whereas extroverts tend to act as bridges between more communities, which are on average smaller and of varying cohesion.