In recent years, social networks have attracted many users' interests. People express their daily experiences and emotions through social networks and become aware of others interests and thoughts. In these networks, influential users play an important role in broadcasting information to their communities. As a result, discovering such users in social networks has become very important, in particular, for marketing purposes. Various solutions already exist for identifying influential users, most of which are structure-based, in that they investigate the influence of a user according to his location in the network graph. This paper proposes a novel approach for identifying influential users on Instagram, by examining User Generated Contents (UGC). More specifically, the proposed method combines various types of features extracted from the images posted on Instagram to determine whether or not a user is influential, without requiring any information about the structure of the network. An extensive set of experiments are performed to validate the effectiveness of the proposed method in identifying influential users.