ExplainingDelta

This repository provides R code and data sets for the experiments underlying

Evert, S., Proisl, T., Jannidis, F., Reger, I., Pielström, S., Schöch, C., and Vitt, T. (2017). Understanding and explaining Delta measures for authorship attribution. Digital Scholarship in the Humanities, 22(suppl_2): ii4--ii16.

as well as many further investigations that did not fit into the paper.

Prerequisites

• a recent version of R

• RStudio is strongly recommended for exceuting the RMarkdown notebooks

• these add-on packages

  • ape
  • cluster (should be pre-installed with R)
  • colorspace
  • corpora
  • ggplot2
  • knitr
  • MASS (should be pre-installed with R)
  • pvclust
  • matrixStats
  • tsne
  • wordspace

• you can install all necessary packages with the R command

  install.packages(c("ape", "cluster", "colorspace", "corpora", "ggplot2", "knitr", "MASS", "pcvlust", "matrixStats", "tsne", "wordspace"))

Overview of notebooks

• delta_tools.Rmd: utility functions for experiments (automatically converted to delta_tools.R and imported by other notebooks)
• dsh_2016.Rmd: replication and plots for Evert et al. (2017)
• delta_theory.Rmd: mathematical notation and some background on Delta measures
• delta_scaling.Rmd: experiments on feature selection and feature scaling
• delta_normalization.Rmd: experiments on vector normalization
• delta_clustering.Rmd: experiments with different clustering algorithms
• delta_understanding.Rmd: understanding Burrows Delta and its variants
• delta_significance.Rmd: measuring the statistical significance of Delta-based authorshop attribution