• 2024

    Research article in proceedings (conference)

    Stampe, L., Lütke-Stockdiek, J., Grimme, B., & Grimme, C. (2024). Benchmarking Sentence Embeddings in Textual Stream Clustering with Applications to Campaign Detection. In Proceedings of the IEEE World Congress on Computational Intelligence, Yokohama. (accepted / in press (not yet published))
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  • 2023

    Research article in proceedings (conference)

    Grimme, B., Pohl, J., Winkelmann, H., Stampe, L., & Grimme, C. (2023). Lost in Transformation: Rediscovering LLM-Generated Campaigns in Social Media. In Ceolin, D., Caselli, T., & Tulin, M. (Eds.), Disinformation in Open Online Media (pp. 72–87). Lecture Notes in Computer Science: Vol. 14397. Amsterdam, Niederlande: Springer.
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    Stampe, L., Pohl, J., & Grimme, C. (2023). Towards Multimodal Campaign Detection: Including Image Information in Stream Clustering to Detect Social Media Campaigns. In Ceolin, D., Caselli, T., & Tulin, M. (Eds.), Disinformation in Open Online Media (pp. 144–159). Lecture Notes in Computer Science: Vol. 14397. Amsterdam: Springer.
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  • 2022

    Abstract in edited proceedings (conference)

    Stampe, L., & Hellingrath, B. (2022). Digitalization of Supply Chain Risk Management — Eliciting Potential and Barriers with Qualitative Interviews.
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  • 2021

    Research article (book contribution)

    Stampe, L., & Hellingrath, B. (2021). Risk Indicators and Data Analytics in Supply Chain Risk Monitoring. In Buscher, U., Lasch, R., & Schönberger, J. (Eds.), Logistics Management (pp. 246–263). Lecture Notes in Logistics. Dresden: Springer.
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