Advertisement

Automatic Author Attribution for Short Text Documents

  • Monika Nawrot
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6562)

Abstract

This paper presents the results of studies on author attribution for short text documents. It briefly presents features used in authorship identification, outlines the proposed hybrid algorithm, and describes the results of experiments which explore conditions needed to reliably recognize author identity. Finally, it summarizes obtained results, presents main problems faced while authorship attribution for short text documents and proposes improvements which when applied might lead to the better authorship description and in consequence recognition.

Keywords

authorship analysis author attribution statistical stylistic support vector machine 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Corney, M.: Analysing E-mail Text Authorship for Forensic Purposes (2003)Google Scholar
  2. 2.
    Dabagh, R.M.: Authorship Attribution and Statistical Text Analysis (2007)Google Scholar
  3. 3.
    de Vel, O., Corney, M., Anderson, A., Mohay, G.: Language and Gender Author Cohort Analysisof E-mail for Computer Forensics (2002)Google Scholar
  4. 4.
    Grieve, J.W.: Quantitative Authorship Attribution: A History and an Evaluation of Techniques (2005)Google Scholar
  5. 5.
    Kłopotek, M.A.: Inteligentne wyszukiwarki internetowe (2001)Google Scholar
  6. 6.
    Carvalho, V.R., Cohen, W.W.: Learning to Extract Signature and Reply Lines from Email (2004)Google Scholar
  7. 7.
    Schler, J., Koppel, M., Argamon, S., Pennebaker, J.: Effects of Age and Gender on Blogging (2005)Google Scholar
  8. 8.
    Rayson, P., Leech, G., Hodgens, M.: Social differentiation in use of English vocabulary: some analyses of the conversational component of the British national corpus1 (1997)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Monika Nawrot
    • 1
  1. 1.The University of Science and Technology AGHKrakowPoland

Personalised recommendations