Discovering Author Groups using a B-compact graph-based Clustering

Identifying the authorship either of an anonymous or a doubtful document constitutes a cornerstone for automatic forensic applications. Moreover, it is a challenging task for both humans and computers. Clustering documents according to the linguistic style of the authors who wrote them has been a task little studied by the research community. In order to address this problem, PAN Evaluation Framework has become the first effort to promote the development of the author clustering. This article proposes a graph-based method, specifically βcompact clustering, for discovering the groups of documents written by the same author. The β-compact algorithm is based on the analysis of the similarity between documents and they belong to the same group as long as the similarity between them exceeds the threshold β and it is the maximum similarity with respect to other documents. In our proposal we evaluated different linguistic features and similarity measures presented in previous works of authorship analysis task. The training dataset was used to determine the best value of β parameter for each language. The result of the experiments was encouraging.