Skip to main content
Springer Nature Link
Log in

Consonance as a Stylistic Feature for Authorship Attribution of Historical Texts

  • Conference paper
  • First Online:
Text, Speech, and Dialogue (TSD 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11697))

Included in the following conference series:

  • 878 Accesses

Abstract

We present an investigation of the usefulness of consonance as a stylistic feature for author attribution of historical texts. We describe an algorithm for extracting consonance from written text and a set of experiments using different classifiers to explore the accuracy of consonance-based attribution on a set of 18th-century documents and a collection of 19th-century literary works.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Abbasi, A., Chen, H.: Applying authorship analysis to extremist group web forum messages. IEEE Intell. Syst. 20(5), 67–75 (2005)

    Article  Google Scholar 

  2. Addanki, K., Wu, D.: Unsupervised rhyme scheme identification in hip hop lyrics using hidden Markov models. In: Dediu, A.-H., Martín-Vide, C., Mitkov, R., Truthe, B. (eds.) SLSP 2013. LNCS (LNAI), vol. 7978, pp. 39–50. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-39593-2_3

    Chapter  Google Scholar 

  3. Agrawal, M., Gonçalves, T.: Age and gender identification using stacking for classification. PAN at CLEF 2016. In: Balog, K., et al. (eds.) CLEF 2016 Eval. Labs and Workshop, 16 September, Evora, Portugal. CEUR-WS.org (2016). ISSN 1613–0073

    Google Scholar 

  4. Barquist, C., Shie, D.: Computer analysis of alliteration in Beowulf using distinctive feature theory. Literary Linguist. Comput. 6(4), 274–280 (1991)

    Article  Google Scholar 

  5. Binongo, J.N.G.: Who wrote the 15th book of Oz? An application of multivariate statistics to authorship attribution. Comput. Linguist. 16(2), 9–17 (2003)

    MathSciNet  Google Scholar 

  6. Burrows, J.: A second opinion on Shakespeare and authorship studies in the twenty-first century. Shakesp. Q. 63(3), 355–92 (2012)

    Article  Google Scholar 

  7. Burrows, J.: Computation into Criticism: A Study of Jane Austen’s Novels and an Experiment in Method. Clarendon Press, Oxford (1987)

    Google Scholar 

  8. Craig, H., Kinney, A. (eds.): Shakespeare, Computers and the Mystery of Authorship. Cambridge University Press, Cambridge (2009)

    Google Scholar 

  9. deVel, O., Anderson, A., Corney, M., Mohay, G.M.: Mining e-mail content for author identification forensics. SIGMOD Rec. 30(4), 55–64 (2001)

    Article  Google Scholar 

  10. Dumalus, A., Fernandez, P.: Authorship attribution using writer’s rhythm based on lexical stress. In: 11th Philippine Computing Science Congress, Naga City, Philippines (2011)

    Google Scholar 

  11. Ucelay, J.G., et al.: Profile-based approach for age and gender identification-PAN at CLEF 2016. In: Balog, K., et al. (eds.) CLEF 2016 Eval. Labs and Workshop, 16 September Evora, Portugal. CEUR-WS.org (2016). ISSN 1613–0073

    Google Scholar 

  12. Gungor, A.: Benchmarking authorship attribution techniques using over a thousand books by fifty victorian era novelists. Purdue Master of Thesis (2018)

    Google Scholar 

  13. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.: The WEKA data mining software: an update. SIGKDD Explor. 11(1), 10–18 (2009)

    Article  Google Scholar 

  14. Hoover, D.: Authorship attribution variables and victorian drama: words, word-ngrams, and character-ngrams. In: Proceedings of DH 2018, 18 June, Mexico City, Mexico, pp. 212–214 (2017)

    Google Scholar 

  15. Ivanov, L.: Learning patterns of assonance for authorship attribution of historical texts: FLAIRS-32, Sarasota, FL, USA, vol. 5, no. 19, pp. 191–196 (2019)

    Google Scholar 

  16. Ivanov, L., Aebig, A., Meerman, S.: Lexical stress-based authorship attribution with accurate pronunciation patterns selection. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds.) TSD 2018. LNCS (LNAI), vol. 11107, pp. 67–75. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00794-2_7

    Chapter  Google Scholar 

  17. Ivanov, L.: Using alliteration in authorship attribution of historical texts. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds.) TSD 2016. LNCS (LNAI), vol. 9924, pp. 239–248. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-45510-5_28

    Chapter  Google Scholar 

  18. Ivanov, L., Petrovic, S.: Using lexical stress in authorship attribution of historical texts. In: Král, P., Matoušek, V. (eds.) TSD 2015. LNCS (LNAI), vol. 9302, pp. 105–113. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-24033-6_12

    Chapter  Google Scholar 

  19. Jackson, M.D.: Determining the Shakespeare Canon: Arden of Faversham and A Lover’s Complaint. Oxford University Press, Oxford (2014)

    Book  Google Scholar 

  20. Jackson, M.D.: New research on the dramatic canon of Thomas Kyd. Res. Oppor. Medieval Renaiss. Drama 47, 107–127 (2008)

    Google Scholar 

  21. Juola, P.: JGAAP: a system for comparative evaluation of authorship attribution. J. Chicago Colloq. Digit. Hum. Comput. Sci. 1(1), 1–5 (2009)

    MathSciNet  Google Scholar 

  22. Kotzé, E.: Author identification from opposing perspectives in forensic linguistics. Southern Afr. Linguist. Appl. Lang. Stud. 28(2), 185–197 (2010)

    Article  Google Scholar 

  23. Kuznetsov, M., Motrenko, A., Kuznetsova, R., Strijov, V.: Methods for intrinsic plagiarism detection and author diarization-PAN at CLEF 2016. In Balog, K., et al. (eds.) CLEF 2016 Eval. Labs and Workshop, 16 September, Evora, Portugal. CEUR-WS.org (2016). ISSN 1613–0073

    Google Scholar 

  24. Lewis, D., Yang, Y., Rose, T., Li, F.: RCV1: a new benchmark collection for text categorization research. J. Mach. Learn. Res. 5, 361–397 (2004)

    Google Scholar 

  25. Lowe, D., Matthews, R.: Shakespeare vs. Fletcher: a stylometric analysis by radial-basis functions. Comput. Hum. 29, 449–461 (1995)

    Article  Google Scholar 

  26. Morton, A.: The authorship of Greek prose. J. Roy. Stat. Soc. 128, 169–233 (1965)

    Article  Google Scholar 

  27. Mosteller, W.: Inference and Disputed Authorship: The Federalist. AWL, Reading (1964)

    MATH  Google Scholar 

  28. NIST. https://trec.nist.gov/data/reuters/reuters.html

  29. Ogaltsov, A., Romanov, A.: Language variety and gender classification for author profiling in PAN 2017 - PAN at CLEF 2017. In: Cappellato, L., et al. (eds.) CLEF 2017 Eval. Labs and Workshop, 17 September, Dublin, Ireland. CEUR-WS.org (2017). ISSN 1613–0073

    Google Scholar 

  30. Petrovic, S., Berton, G., Campbell, S., Ivanov, L.: Attribution of 18th century political writings using machine learning. J. Technol. Soc. 11(3), 1–13 (2015)

    Google Scholar 

  31. Petrovic, S., Berton, G., Schiaffino, R., Ivanov, L.: Examining the Thomas Paine corpus: automated computer author attribution methodology applied to Thomas Paine’s writings. In: Cleary, S., Stabell, I. (eds.) New Directions in Thomas Paine Studies, edn. 1. Palgrave Macmillan, USA (2016). https://doi.org/10.1057/9781137589996_3

    Google Scholar 

  32. Petrovic, S., Berton, G., Schiaffino, R., Ivanov, L.: Authorship attribution of Thomas Paine works. In: Proceedings of the International Conference on Data Mining DMIN 2014, pp. 182–188 (2014). ISBN: 1-60132-267-4

    Google Scholar 

  33. Smith, M.W.A.: An investigation of Morton’s method to distinguish Elizabethan playwrights. Comput. Hum. 19, 3–21 (1985)

    Article  Google Scholar 

  34. Sousa-Silva, R.: Detecting translingual plagiarism: a forensic linguistic contribution to computational processing (2016). http://www.uniweimar.de/medien/webis/events/pan-16

  35. Stamatatos, E.: Authorship verification: a review of recent advances. Re. Comput. Sci. 123, 9–25 (2016)

    Google Scholar 

  36. Stamatatos, E.: A survey of modern authorship attribution methods. J. Am. Soc. Inform. Sci. Technol. 60(3), 538–556 (2009)

    Article  Google Scholar 

  37. Tellez, E., Miranda-Jiménez, S., Graff, M., Moctezuma, D.: Gender and language-variety identification with MicroTC-PAN at CLEF 2017. In: Cappellato, L., et al. (eds.) CLEF 2017 Eval. Labs and Workshop, 17 September, Dublin, Ireland. CEUR-WS.org (2017). ISSN 1613–0073

    Google Scholar 

  38. University of California Irvine Machine Learning Repository. https://archive.ics.uci.edu/ml/datasets/Victorian+Era+Authorship+Attribution

Download references

Author information

Authors and Affiliations

  1. Computer Science Department, Iona College, 715 North Ave., New Rochelle, NY, 10801, USA

    Lubomir Ivanov & Brandon Neilsen

Authors
  1. Lubomir Ivanov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Brandon Neilsen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lubomir Ivanov .

Editor information

Editors and Affiliations

  1. University of West Bohemia, Pilsen, Czech Republic

    Kamil Ekštein

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ivanov, L., Neilsen, B. (2019). Consonance as a Stylistic Feature for Authorship Attribution of Historical Texts. In: Ekštein, K. (eds) Text, Speech, and Dialogue. TSD 2019. Lecture Notes in Computer Science(), vol 11697. Springer, Cham. https://doi.org/10.1007/978-3-030-27947-9_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-27947-9_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27946-2

  • Online ISBN: 978-3-030-27947-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation