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. 2016 Aug 29;16(9):1374.
doi: 10.3390/s16091374.

Automatic Authorship Detection Using Textual Patterns Extracted from Integrated Syntactic Graphs

Helena Gómez-Adorno  1 , Grigori Sidorov  2 , David Pinto  3 , Darnes Vilariño  4 , Alexander Gelbukh  5
Affiliations

Automatic Authorship Detection Using Textual Patterns Extracted from Integrated Syntactic Graphs

Helena Gómez-Adorno et al. Sensors (Basel). .

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.

Keywords: authorship attribution; authorship verification; integrated syntactic graphs; shortest paths walks; syntactic n-grams; textual patterns.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Dependency trees of three sentences of the target text using word_POS combination for the nodes and dependency labels for the edges.
Figure 2
Figure 2
The integrated syntactic graph for the three sentences shown in Figure 1.
Figure 3
Figure 3
Syntactic tree with the synonym expansion of a sentence: “Yes, here they come”.
Figure 4
Figure 4
Accuracy for each of the ten authors.
See this image and copyright information in PMC

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