Automatic Authorship Detection Using Textual Patterns Extracted from Integrated Syntactic Graphs

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 short...

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Bibliographic Details
Main Authors: Helena Gómez-Adorno, Grigori Sidorov, David Pinto, Darnes Vilariño, Alexander Gelbukh
Format: Article
Language:English
Published: MDPI AG 2016-08-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/16/9/1374
Description
Summary: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 documents. On average, our method outperforms the state of the art approaches and gives consistently high results across different corpora, unlike existing methods. Our results show that our textual patterns are useful for the task of authorship attribution.
ISSN:1424-8220