Abstract
In this paper we present an authorship attribution method based on the use of complete (non-continuous, with bifurcations) syntactic n-grams as style markers. Syntactic n-grams are obtained by following paths in subtrees of a syntactic tree. We work with relatively short text fragments and build authors’ profiles of various sizes using tf-idf scheme. We train SVM classifier to perform the task. We compare the method with the application of character n-grams and show that the accuracy increases when using complete syntactic n-grams.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Argamon, S., Juola, P.: Overview of the international authorship identification competition at pan-2011. In: CLEF (Notebook Papers/Labs/Workshop) (2011)
Bozkurt, I.N., Baghoglu, O., Uyar, E.: Authorship attribution. In: 22nd International Symposium on Computer and information sciences, ISCIS 2007, pp. 1–5. IEEE (2007)
Chang, C.C., Lin, C.J.: Libsvm: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology (TIST) 2(3), 27 (2011)
Diederich, J., Kindermann, J., Leopold, E., Paass, G.: Authorship attribution with support vector machines. Applied intelligence 19(1-2), 109–123 (2003)
Escalante, H.J., Solorio, T., Montes-y Gómez, M.: Local histograms of character n-grams for authorship attribution. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, vol. 1, pp. 288–298. Association for Computational Linguistics (2011)
Halteren, H.V.: Author verification by linguistic profiling: An exploration of the parameter space. ACM Transactions on Speech and Language Processing (TSLP) 4(1), 1 (2007)
Holmes, D.I., Forsyth, R.S.: The federalist revisited: New directions in authorship attribution. Literary and Linguistic Computing 10(2), 111–127 (1995)
Juola, P.: Future trends in authorship attribution. In: Advances in digital forensics III, pp. 119–132. Springer (2007)
Klein, D., Manning, C.D.: Accurate unlexicalized parsing. In: Proceedings of the 41st Annual Meeting on Association for Computational Linguistics, vol. 1, pp. 423–430. Association for Computational Linguistics (2003)
Sidorov, G.: Non-continuous syntactic n-grams. Polibits 48, 67–75 (2013)
Sidorov, G.: Syntactic dependency based n-grams in rule based automatic english as second language grammar correction. International Journal of Computational Linguistics and Applications 4(2), 169–188 (2013)
Sidorov, G., Velasquez, F., Stamatatos, E., Gelbukh, A., Chanona-Hernández, L.: Syntactic n-grams as machine learning features for natural language processing. Expert Systems with Applications 41(3), 853–860 (2014)
Stamatatos, E.: A survey of modern authorship attribution methods. Journal of the American Society for information Science and Technology 60(3), 538–556 (2009)
Tweedie, F.J., Singh, S., Holmes, D.I.: Neural network applications in stylometry: The federalist papers. Computers and the Humanities 30(1), 1–10 (1996)
Zhao, Y., Zobel, J., Vines, P.: Using relative entropy for authorship attribution. In: Information Retrieval Technology, pp. 92–105. Springer (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Posadas-Duran, JP., Sidorov, G., Batyrshin, I. (2014). Complete Syntactic N-grams as Style Markers for Authorship Attribution. In: Gelbukh, A., Espinoza, F.C., Galicia-Haro, S.N. (eds) Human-Inspired Computing and Its Applications. MICAI 2014. Lecture Notes in Computer Science(), vol 8856. Springer, Cham. https://doi.org/10.1007/978-3-319-13647-9_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-13647-9_2
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13646-2
Online ISBN: 978-3-319-13647-9
eBook Packages: Computer ScienceComputer Science (R0)