Advertisement

Authorship Attribution by Functional Discriminant Analysis

  • Chahrazed KettafEmail author
  • Abderrahmane Yousfate
Conference paper
  • 20 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11989)

Abstract

Recognizing the author of a given text is a very difficult task that relies on several complicated and correlated criterias. For this purpose, several classification methods are used (neuronal network, discriminant analysis, SVM...). But a good representation of the text that keeps the maximum of the stylistic information is very important and has a considerable influence on the result. In this paper, we will tackle the problem of the authorship attribution for very long texts using the discriminant analysis extended to the functional case after presenting the texts as elements of a separable Hilbert space.

Keywords

Authorship attribution Textmining Big textual data Discriminant analysis Funtional classification Functional data analysis 

References

  1. 1.
    Preda, C.: L’approche PLS pour l’analyse de données fonctionnelles. Bull. Soc. Sci. Méd. 2, 171–185 (2006)Google Scholar
  2. 2.
    Zheng, R., Li, J., Chen, H., Huang, Z.: A framework for authorship identification of online messages: writing style features and classification techniques. J. Am. Soc. Inf. Sci. Technol. 57, 378–393 (2006)CrossRefGoogle Scholar
  3. 3.
    Kjell, B.: Discrimination of authorship using visualization. Inf. Process. Manage. 30, 141–150 (1994)CrossRefGoogle Scholar
  4. 4.
    Hastie, T., Ruja, A., Tibshirani, R.: Penalized discriminant analysis. Ann. Stat. 23, 73–102 (1995)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Grieve, J.: Quantitative authorship attribution: an evaluation of techniques. Lit. Linguist. Comput. 22, 251–270 (2007)CrossRefGoogle Scholar
  6. 6.
    Holmes, D.I.: Authorship attribution. Comput. Humanit. 28, 87–106 (1994)CrossRefGoogle Scholar
  7. 7.
    Stamatatos, E., Fakotakis, N., Kokkinakis, G.: Automatic text categorization in terms of genre and author. Comput. Linguist. 26, 471–495 (2000)CrossRefGoogle Scholar
  8. 8.
    Burrows, J.F.: Word patterns and story shapes: the statistical analysis of narrative style. Lit. Linguist. Comput. 2, 61–70 (1987)CrossRefGoogle Scholar
  9. 9.
    Argamon, S., Levitan, S.: Measuring the usefulness of function words for authorship attribution. In: Proceedings of the Joint Conference of the Association for Computers and the Humanities and the Association for Literary and Linguistic Computing (2005)Google Scholar
  10. 10.
    de Vel, O., Anderson, A., Corney, M., Mohay, G.: Mining e-mail content for author identification forensics. ACM SIGMOD Rec. 30, 55–64 (2001) CrossRefGoogle Scholar
  11. 11.
    Forsyth, R., Holmes, D.: Feature-finding for text classification. Lit. Linguist. Comput. 11, 163–174 (1996)CrossRefGoogle Scholar
  12. 12.
    Baayen, R., van Halteren, H., Tweedie, F.: Outside the cave of shadows: using syntactic annotation to enhance authorship attribution. Lit. Linguist. Comput. 11, 121–132 (1996)CrossRefGoogle Scholar
  13. 13.
    Gamon, M.: Linguistic correlates of style: authorship classification with deep linguistic analysis features. In: Proceedings of the 20th International Conference on Computational Linguistics (2004)Google Scholar
  14. 14.
    McCarthy, P.M., Lewis, G.A., Dufty, D.F., McNamara, D.S.: Analyzing writing styles with Coh-Metrix. In: Proceedings of the Florida Artificial Intelligence Research Society International Conference (2006)Google Scholar
  15. 15.
    Fellbaum, C.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge (1998)CrossRefGoogle Scholar
  16. 16.
    Forman, G.: An extensive empirical study of feature selection metrics for text classification. J. Mach. Learn. Res. 3, 1289–1305 (2003)zbMATHGoogle Scholar
  17. 17.
    Argamon, S., Whitelaw, C., Chase, P., Hota, S.R., Garg, N., Levitan, S.: Stylistic text classification using functional lexical features. J. Am. Soc. Inform. Sci. Technol. 58, 802–822 (2007)CrossRefGoogle Scholar
  18. 18.
    Posadas-Durán, J.P., Gómez-Adorno, H., Sidorov, G.: Application of the distributed document representation in the authorship attribution task for small corpora. Soft Comput. 21, 627–639 (2017). American Society for Information Science and TechnologyCrossRefGoogle Scholar
  19. 19.
    Schmidt, H.: Probabilistic part-of-speech tagging using decision trees (1994)Google Scholar
  20. 20.
    Akimushkin, C., Amancio, D.R., Oliveira, O.N.: On the role of words in the network structure of texts: application to authorship attribution. Phys. A (2017).  https://doi.org/10.1016/j.physa.2017.12.054CrossRefGoogle Scholar
  21. 21.
    Stamatatos, E., Koppel, M.: Plagiarism and authorship analysis: introduction to the special issue (2016). http://www.jstor.org/stable/41486024

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Laboratoire de MathématiquesDjillali Liabes UniversitySidi Bel AbbesAlgeria

Personalised recommendations