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Center for Data and Simulation Science

Automatic processing of natural language in all its facets is the core research interest of Nils Reiter and his research group. The history of natural language process and computational linguistics go back to the 1960s and quite diverse methods have been applied to this problem in the past. Since roughly 2000, more and more practical applications and research systems are built using machine learning systems, because the number of (potentially) influencing contextual factors for making decisions in language is enormeous and very difficult to take into account manually.

Nils Reiter’s work is specifically focused on applications of computational linguistics methods and best practices on research data and research problems in the humanities and social sciences: With team members and collaboration partners, he works on the quantitative analysis of dramatic texts and theater plays, the automatic understanding of narrative texts and story telling and generally methods to combine qualitative and quantitative research.

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Influential factors and their contribution to the classification performance for determining whether dramatic characters in 18th and 19th century German plays fulfill the role of ‘intriguer’. Details can be found in https://dx.doi.org/10.17175/2020_007.

Selected publications

  1. Axel Pichler, Janis Pagel, Nils Reiter. “Evaluating LLM-Prompting for Sequence Labeling Tasks in Computational Literary Studies”. In Proceedings of the 9th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2025), May 2025.
  2. Janis Pagel, Axel Pichler, Nils Reiter. “Evaluating In-Context Learning for Computational Literary Studies: A Case Study Based on the Automatic Recognition of Knowledge Transfer in German Drama”. In Proceedings of the 8th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2024), March 2024.
  3. Patrick Brookshire, Nils Reiter. “Modeling Moravian Memoirs: Ternary Sentiment Analysis in a Low Resource Setting”. In Proceedings of the 8th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2024), March 2024.
  4. Melanie Andresen, Nils Reiter (eds.). “Computational Drama Analysis. Reflecting on Methods and Interpretations”, 2024.
  5. Nils Reiter, Marcus Willand. “What are they talking about? A Systematic Exploration of Theme Identification Methods for Character Speech in Dramatic Texts”. In Fotis Jannidis (ed.): Digitale Literaturwissenschaft, pp. 473-508, Stuttgart 2023.
  6. Elke Smith, Simon Michalski, Kilian H. K. Knauth, Kai Kaspar, Nils Reiter, Jan Peters. “Large‑Scale Web Scraping for Problem Gambling Research: A Case Study of COVID‑19 Lockdown Effects in Germany”. Journal of Gambling Studies, 2023.
  7. Axel Pichler, Nils Reiter. “From Concepts to Texts and Back: Operationalization as a Core Activity of Digital Humanities”. Journal of Cultural Analytics, 7(4), 2022.
  8. Stephanie Siewert, Nils Reiter. “The Explorative Value of Computational Methods: Rereading the American Short Story”. American Studies, 63(2), pp. 199-230, 2018.