In real-world complex networks nodes are generally arranged in tightly knit groups that are loosely connected one to each other. Such groups are called communities. Community members are generally admitted to share common proprieties. Hence, unfolding the community structure of a network could give us many insights about the overall structure of the network. This problem has attracted much of attention in past years. Most of existing approaches are designed for static simple networks, where all edges are of the same type. However, real networks are often heterogeneous and dynamic. The concept of multiplex networks has been introduced in order to ease modeling such networks. In this work, we present a survey study on main approaches for community detection in monoplex and multiplex networks.