Automatic authorship detection using textual patterns extracted from integrated syntactic graphs

Helena Gómez-Adorno, Grigori Sidorov, David Pinto, Darnes Vilariño, Alexander Gelbukh

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

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.

Original languageEnglish
Article number1374
JournalSensors (Switzerland)
Volume16
Issue number9
DOIs
StatePublished - Sep 2016

Keywords

  • Authorship attribution
  • Authorship verification
  • Integrated syntactic graphs
  • Shortest paths walks
  • Syntactic n-grams
  • Textual patterns

Fingerprint

Dive into the research topics of 'Automatic authorship detection using textual patterns extracted from integrated syntactic graphs'. Together they form a unique fingerprint.

Cite this