wiki:private/AdvancedNlpCourse/Stylometry

Version 10 (modified by Jan Rygl, 6 years ago) (diff)

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Stylometry

IA161 Advanced NLP Course, Course Guarantee: Aleš Horák

Prepared by: Honza Rygl

State of the Art

The analysis of author's characteristic writing style and vocabulary has been used to uncover author's traits such as authorship, age, or gender documents by both manual linguistic approaches and automatic algorithmic methods.

The most common approach to stylometry problems is to combine stylistic analysis with machine learning techniques:

  1. specific style markers are extracted,
  2. a classification procedure is applied to extracted markers

References

  1. Stamatatos, E. (2009), A Survey of Modern Authorship Attribution Methods (2009), Journal of the American Society for Information Science and Technology, 60(3), 538-556. pdf
  2. Kestemont, M. (2014), Function Words in Authorship Attribution From Black Magic to Theory? Proceedings of the 3rd Workshop on Computational Linguistics for Literature, EACL 2014, 59–66 pdf
  3. Walter, D. Explanation in Computational Stylometry

Practical Session

Student will get to know a *Style & Identity Recognition* tool. They will test this tool on prepared data. Their goal will be to implement a small function to extract style markers from a text.

  1. go to asteria04.fi.muni.cz server:
    ssh asteria04.fi.muni.cz
    
  2. Download a python package https://github.com/janrygl/sir/archive/assignment.zip
    wget https://github.com/janrygl/sir/archive/assignment.zip
    
  3. Unzip a downloaded file
    unzip assignment.zip
    
  4. Go to an unziped folder
    cd sir-assignment
    
  5. Test a program
    ./run.sh
    

Faster way:

wget https://github.com/janrygl/sir/archive/assignment.zip; unzip assignment.zip; cd sir-assignment
./run.sh