Josef Ruppenhofer

Deutsch

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.

Why CATALPA?

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.

    • since 03.2023 Postdoctoral researcher in the project DAKODA
    • 08.2018 - 02.2023: co-lead of the Archive for Spoken German, Leibniz-Institute for the German Language, Mannheim
    • 05. 2016 - 07. 2018: Group lead for the area of Sentiment Analysis, Leibniz ScienceCampus, Leibniz-IDS/Universität Heidelberg
    • 05.2011 - 04.2016: Postdoctoral researcher, Institute for Information Science and Language Technology, Hildesheim University
    • 07.2008 - 03.2011: Postdoctoral researcher, Dept. of Computational Linguistics, Saarland University, Saarbrücken
    • 01. 2007 - 06.2008: Intelligent Systems Program, University of Pittsburgh
    • 01.2005 – 01.2006: Postdoctoral researcher, FrameNet project, International Computer Science Institute, Berkeley. CA
    • 12.2004 Phd in Linguistics, University of California at Berkeley
    • 12.1999 MA in Linguistics, University of California at Berkeley
    • 05.1997 MA in Linguistics, University of Colorado at Boulder

    • 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

    Journals

    • 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. https://doi.org/10.6093/GERMANICA.V0I33.10752

    Conferences

    • Ruppenhofer, J., Schwendemann, M., Portmann, A., Wisniewski, K., & Zesch, T. (2024). Every verb in its right place? A roadmap for operationalizing developmental stages in the acquisition of L2 German. In N. Calzolari, M.-Y. Kan, V. Hoste, A. Lenci, S. Sakti, & N. Xue (Eds.), Proceedings of the 2024 joint international conference on computational linguistics, language resources and evaluation (LREC-COLING 2024) (pp. 6655–6670). ELRA; ICCL. https://aclanthology.org/2024.lrec-main.589

    2023

    Journals

    • 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). https://doi.org/10.48694/kordaf.3845

    Conferences

    • 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. https://doi.org/10.18653/v1/2023.emnlp-main.1012

    2022

    Journals

    • 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. https://doi.org/10.1007/s10579-022-09581-9

Research Professorship Computational Linguistics | 02.07.2024