Abstract
This paper presents some early results from a comprehensive project, whose goal is to investigate the use of intonation and lexical stress in authorship attribution. We demonstrate how lexical stress patterns extracted from written text can be used to train a variety of machine learning algorithms to perform attribution of texts of unknown or disputed authorship. Specifically, we apply our methodology to a collection of 18\(^\mathrm{th}\) century American and British political writings, and demonstrate how combining lexical stress with other lexical features can significantly improve the attribution results.
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
Love, H.: Attributing Authorship: An Introduction. Cambridge University Press, Cambridge (2002)
Stamatatos, Efstathios: A survey of modern authorship attribution methods. Journal of the American Society for Information Science and Technology 60(3), 538–556 (2009)
Lowe, D., Matthews, R.: Shakespeare vs. Fletcher: A Stylometric Analysis by Radial Basis Functions. Computers and the Humanities 29, 449–461 (1995)
Matthews, R., Merriam, T.: Neural computation in stylometry: An application to the works of Shakespeare and Fletcher. Literary and Linguistic Computing 8(4), 203–209 (1993)
Burrows, J.: Computation into Criticism: A Study of Jane Austen’s Novels and an Experiment in Method. Clarendon Press, Oxford (1987)
Morton, A.Q.: The Authorship of Greek Prose. Journal of the Royal Statistical Society (A) 128, 169–233 (1965)
Mosteller, F., Wallace, D.: Inference and Disputed Authorship: The Federalist. Addison-Wesley, Reading (1964)
Petrovic, S., Berton, G., Schiaffino, R., Ivanov, L.: Authorship attribution of Thomas Paine works. In: Interdisciplinary Social Sciences Conference, Prague, Czech Republic (2013)
Petrovic, S., Berton, G., Schiaffino, R., Ivanov, L.: Authorship attribution of Thomas Paine works. International Conference on Data Mining DMIN 2014, pp. 182–188. Springer, Heidelberg (2014)
Chomsky, N., Morris, H.: The sound pattern of English. New York (1968)
Fudge, E.: English word-stress. London (1984)
Creel, S., Tanenhaus, M., Aslin, R.: Consequences of Lexical Stress on Learning an Artificial Lexicon. Journal of Experimental Psychology: Learning, Memory, and Cognition 32(1), 15–32 (2006)
Argamon, S., Whitelaw, C., Chase, P., Raj Hota, S., Garg, N., Levitan, S.: Stylistic Text Classification Using Functional Lexical Features. Journal of the American Society for Information Science and Technology 58(6), 802–822 (2007)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.: The WEKA Data Mining Software: An Update. SIGKDD Explorations 11(1) (2009)
Juola, P.: Authorship Attribution. Foundations and Trends in Information Retrieval 1(3), 233–334 (2006)
Toutanova, K., Klein, D., Manning, C.: Feature-rich part-of-speech tagging with a cyclic dependency network. In: HLT-NAACL, pp. 252–259 (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Ivanov, L., Petrovic, S. (2015). Using Lexical Stress in Authorship Attribution of Historical Texts. In: Král, P., Matoušek, V. (eds) Text, Speech, and Dialogue. TSD 2015. Lecture Notes in Computer Science(), vol 9302. Springer, Cham. https://doi.org/10.1007/978-3-319-24033-6_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-24033-6_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24032-9
Online ISBN: 978-3-319-24033-6
eBook Packages: Computer ScienceComputer Science (R0)