Great authors of fiction and theatre have the capacity of creating memorable characters that take life and become almost as real as living persons to the readers/audience. The study of characterization, namely of how this is achieved, is a well-researched topic in corpus stylistics: for instance (Mahlberg, 2012) attempts to identify typical lexical patterns for memorable Dickens’ characters by extracting those lexical bundles that stand out (namely are overrepresented) in comparison to a general corpus. In other works, authorship attribution methods are applied to the different characters of a play to identify whether the author has been able to provide each of them with a “distinct” voice. For instance (Vogel & Lynch, 2008) compare individual Shakespeare characters against the whole play or even against all plays of the same author. The purpose of this paper is to propose a methodology for the study characterization of several characters in French plays of the classical period. The tools developed are meant to support textual analysis by: 1) Verifying the degree of characterization of each character with respect to others. 2) Automatically inducing a list of linguistic features that are significant, representative for that character. Preliminary investigations have been conducted on plays by Moliere, cross-comparing four protagonists from four different plays. The proposed methodology relies on sequential data mining for the extraction of linguistic patterns and on correspondence analysis for comparison of patterns frequencies in each character and for the visual representation of such differences.