Group

We encourage friendly collaboration with colleagues, partners from abroad, and students.

  • Henrik Kragh Sørensen, PI, professor, DSE
  • Mikkel Willum Johansen, associate professor, DSE
  • Josefine Pallavicini, MA, research assistant, DSE
  • Anton Kristian Suhr, MSc, research assistant, DSE
  • Mikkel Tvorup Moseholm, MA, DSE
  • Chris Søndergaard Gassner Nielsen, MSc student, MATH/DSE
  • Stefan Gottlieb Kramer, BSc student, DIKU/DSE
  • Cæcilie Bøje Pedersen, BSc student, MATH/DSE
  • Kristoffer Rank Rasmussen, MSc student, MATH/DSE
  • Sophie Kjeldbjerg Mathiasen, MSc
  • Laura Søvsø Thomasen, PhD, Royal Danish Library
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Collaborators

We collaborate on international, interdisciplinary projects.

  • Hester Breman (Maastricht) and Renee Hoekzema (Oxford) on visual thinking in mathematics
  • Vincent Coumans (Nijmegen) and Ned Wontner (Amsterdam) on evaluations of definitions in mathematics
  • Irida Altman (Zürich) on evolution of Heegaard diagrams

If you are interested in collaboration, see our Contributor- and Authorship guidelines and Contact Us.

Data sources

We can integrate data from a large number of sources:

  • Metadata, pdf-files and LaTeX sources from arXiv
  • Pdf files of research publications
  • Threads from lists on StackExchange
  • Threads in mailing lists such as FOM
  • Reviews from Mathematical Reviews (MathSciNet)
  • Public Twitter feeds
  • Publication networds from Clarivate Web Of Science

Pipelines

We work with a number of corpora with associated pipelines:

  • A pipeline for detecting and measuring mathematical diagrams in pdf files
  • A pipeline for extracting context-structured text from arXiv LaTeX sources
  • A pipeline for accessing metadata and reviews from the Mathematical Reviews
  • A pipeline for analysing 'threaded corpora' such as MathOverflow, mailing lists, etc.

Tools

We deploy a variety of big-data and ML-tools, including:

  • Object detection
  • POS-tagging and linguistic features
  • Dimension reduction (UMAP, PCA)
  • Topic modeling
  • Sentiment analysis

Software

Most of our code is written in python, and we rely on a set of key libraries for LaTeX and XML parsing, NLP, neural networks, statistical analysis, documentation etc.

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Recent publications

Pence, Charles, and Henrik Kragh Sørensen. 2022. “Extending Ourselves? On the Concept and Future of Digital Humanities.” SPSP Newsletter 17 (June). https://sway.office.com/9BAOrK8koNZYYsKe.

Johansen, Mikkel Willum, and Josefine Lomholt Pallavicini. 2022. “Entering the Valley of Formalism: Trends and Changes in Mathematicians’ Publication Practice — 1885 to 2015.” Synthese 200 (3). https://doi.org/10.1007/s11229-022-03741-8.

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If you are interested in our work, please do not hesistate to contact us.