Abstract

                                   Authorship analysis by means of textual features is an important task in linguistic studies.                                    We employ complex networks theory to tackle this disputed problem. In this work, we                                    focus on some measurable quantities of word co-occurrence network of each book for                                    authorship characterization. Based on the network features, attribution probability is                                    defined for authorship identification. Furthermore, two scaling exponents, q-parameter                                    and α -exponent, are combined to classify personal writing style with acceptable high                                    resolution power. The q-parameter, generally known as the nonextensivity measure, is                                    calculated for degree distribution and the α -exponent comes from a power law relationship                                    between number of links and number of nodes in the co-occurrence network constructed                                    for different books written by each author. The applicability of the presented method is                                    evaluated in an experiment with thirty six books of five Persian litterateurs. Our results                                    show high accuracy rate in authorship attribution.