Philip Leifeld
Philip Leifeld


I have written several software packages. An overview is presented below. My main development homepage is my GitHub profile, where you find up-to-date development information and where you can ask questions, file bug reports, look at the documentation, and download the latest versions of my programs.

Discourse Network Analyzer (DNA) and rDNA

The Java software Discourse Network Analyzer (DNA) is a qualitative content analysis tool with network export facilities. You import text files and annotate statements that persons or organizations make, and the program will return network matrices of actors connected by shared concepts. There is also an R package called rDNA for integration with the statistical computing environment R.

You can find lots of information including a user manual, a bibliography, and a YouTube tutorial on the project homepage on GitHub:

Download the software:

Project homepage on GitHub:

Ask questions or report bugs:

I wrote the Discourse Network Analyzer for my PhD project on "Discourse Networks and German pension politics." I won two research awards for this work and an honorable mention from the APSA Political Networks Section. The book was later published as a monograph with the title "Policy Debates as Dynamic Networks" and can be ordered internationally via the University of Chicago Press.

texreg: Conversion of Statistical Model Output in R to LaTeX and HTML Tables

texreg is a package for the statistical computing environment R. It can be used to create tables from regression output (e.g., for publication purposes). The tables are available in several formats: LaTeX, HTML, and ASCII text. They can be embedded directly into documents using Markdown, Pandoc etc.

texreg on CRAN:

Project homepage on GitHub:

Article about texreg in the Journal of Statistical Software:

btergm: Temporal Exponential Random Graph Models (TERGM)

The btergm R package implements the temporal exponential random graph model (TERGM) based on maximum pseudolikelihood estimation (MPLE) with bootstrapped confidence intervals (as described by Desmarais and Cranmer in an article published in Physica A), MCMC-MLE, and Bayesian estimation. The btergm, mtergm, and tbergm functions can be used to estimate statistical network models for longitudinal (panel) data.

btergm on CRAN:

Project homepage on GitHub:

Article about btergm in the Journal of Statistical Software: