Josef Ruppenhofer

Josef Ruppenhofer (Ph.D.) Photo: Hardy Welsch

Josef Ruppenhofer (Ph.D.)

Research assistant at the research professorship "Computational Linguistics" in the project DAKODA

Email: josef.ruppenhofer

Universitätsstraße 27 – PRG / Building 5
Raum B116 / 1. OG
58097 Hagen

What is my role within CATALPA?

As a computational linguist in the project DAKODA, I work on the application of NLP and computational linguistic methods and tools to the study of language acquisition by L2 learners.


Within the DAKODA project at CATALPA, I can contribute to a diverse and interdisciplinary research group that combines applied interests in NLP/CL and language education with theoretically grounded linguistics.

    • NLP for educational applications
    • Corpus linguistics
    • Frame semantics, construction grammar
    • Sentiment analysis, offensive language
  • I am working in the project "DAKODA: Data Competencies in DaF/DaZ: Exploration of Language Technology Approaches for the Analysis of L2 Acquisition Levels in Learner Corpora"

  • 2024


    Flinz, C., & Ruppenhofer, J. (2024). Coreferenza e nuclei tematici nelle interviste del corpus IS. ANNALI. SEZIONE GERMANICA. Rivista Del Dipartimento Di Studi Letterari, Linguistici e Comparati dell’Università degli studi di Napoli L’Orientale, 383–414.



    • Wisniewski, K., Zesch, T., Schwendemann, M., Ruppenhofer, J., & Portmann, A. (2023). Automatische Analysen von Erwerbsstufen in einer großen Lernerkorpus-Datenbank für DaF/DaZ. Das Forschungsprojekt DAKODA. Korpora Deutsch Als Fremdsprache, 3(2).


    • Kupietz, M., Fankhauser, P., & Ruppenhofer, J. (2023). A distributional comparison between FOLK and DeReKo. The Twelfth International Corpus Linguistics Conference 2023. Lancaster University, Monday 3rd-Thursday 6th July, 2023. Book of Abstracts, 155–155.
    • Wiegand, M., Kampfmeier, J., Eder, E., & Ruppenhofer, J. (2023). Euphemistic abuse – a new dataset and classification experiments for implicitly abusive language. In H. Bouamor, J. Pino, & K. Bali (Eds.), Proceedings of the 2023 conference on empirical methods in natural language processing (pp. 16280–16297). Association for Computational Linguistics.



    • Sanguinetti, M., Bosco, C., Cassidy, L., Çetinoğlu, Ö., Cignarella, A. T., Lynn, T., Rehbein, I., Ruppenhofer, J., Seddah, D., & Zeldes, A. (2022). Treebanking user-generated content: A UD based overview of guidelines, corpora and unified recommendations. Language Resources and Evaluation, 57(2), 493–544.