In the last several years, the study of social
networks analysis has gained much interest from the research
community. An active research topic is to investigate the
structure of social networks, i.e. studying the processes that affect
the formation of relationships in a social network. One of the
most fundamental notions governing the structure of social
networks is homophily. This principle provides us with an
illustration of how a network’s surrounding contexts can drive
the formation of its links. Given a particular characteristic of
interest like religion, gender and individuals’ connections, we
concerned to answer to this question “does the network exhibits
homophily according to individuals’ characteristic?” For this
purpose, we proposed a new method that uses fuzzy concepts to
measure social network homophily. In contrast to the traditional
approaches, our method handles non-deterministic information
in homophily detection process. We applied our approach on a
sample dataset drawn from CLOOB social network service. The
experimental results demonstrate our approach reaches good
efficiency.