In this paper we present two different approaches for tackling the authorship attribution task. The first approach uses a set of phrase-level lexicalsyntactic features, whereas the second approach considers a graph-based text representation together with a data mining technique for discovering authorship patterns which may be further used for attributing the authorship of an anonymous document....

Work on authorship attribution has traditionally focused on long texts. In this work, we tackle the question of whether the author of a very short text can be successfully identified. We use Twitter as an experimental testbed. We introduce the concept of an author’s unique “signature”, and show that such signatures are typical of many authors when writing very short texts. We also present a new...

We apply the integrated syntactic graph feature extraction methodology to the task of automatic authorship detection. This graph-based representation allows integrating different levels of language description into a single structure. We extract textual patterns based on features obtained from shortest path walks over integrated syntactic graphs and apply them to determine the authors of docume...

Authorship classification of documents using syntactic features has shown high levels of success; however the complexity in mining syntactic features has generally limited them to a basic feature set (POS tags, rewrite rules). S. Kim et al. [1] have proposed a novel algorithm to generated a set of syntactic features based on frequent subtree patterns of a set of syntactic trees. In this paper, ...

this paper aims to study the performance of the international journal of information science and management (ijism) over a decade using scientometric approach. it also tries to study the                     co-authorship network of authors and institutions using different macro- and micro-level social network analysis metrics. a total of 173 articles published in 23 issues of the ijism covering...