The topic of the paper is to present a novel methodology in order to characterize influential users, such as members of Twitter, as they arise in social networks. The novelty of our approach lies in the fact that we incorporate a set of features for characterizing social media authors, including both nodal and topical metrics, along with new features concerning temporal aspects of user participation on the topic. We also take advantage of cluster-based fusion techniques for retrieved result lists for the ranking of top influential users.