• 2024

    Forschungsartikel in Sammelband (Konferenz)

    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

    Forschungsartikel in Sammelband (Konferenz)

    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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    Klapproth, J., Unger, S., Pohl, J., Boberg, S., Grimme, C., & Quandt, T. (2023). Immunize the Public against Disinformation Campaigns: Developing a Framework for Analyzing the Macrosocial Effects of Prebunking Interventions. In Bui, T. X. (Ed.), Proceedings of the 56th Hawaii International Conference on System Sciences (HICSS) (pp. 2411–2420). Honolulu, HI, USA: ScholarSpace.
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    Pohl, J. S., Markmann, S., Assenmacher, D., & Grimme, C. (2023). Invasion@Ukraine: Providing and describing a Twitter streaming dataset that captures the outbreak of war between Russia and Ukraine in 2022. In Lin, Y.-R., Cha, M., & Quercia, D. (Eds.), Proceedings of the Seventeenth International AAAI Conference on Web and Social Media (pp. 1093–1101). Palo Alto, CA, USA: AAAI Press.
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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

    Forschungsartikel in Sammelband (Konferenz)

    Grimme, C., Pohl, J., Cresci, S., Lüling, R., & Preuss, M. (2022). New Automation for Social Bots: From Trivial Behavior to AI-Powered Communication. In Spezzano, F., Amaral, A., Ceolin, D., Fazio, L., & Serra, E. (Eds.), Proceedings of the 4th Multidisciplinary International Symposium on Disinformation in Open Online Media (MISDOOM) (1st ed., pp. 79–99). Lecture Notes in Computer Science: Vol. 4. Cham, Switzerland: Springer Nature.
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    Pohl, J. S., Assenmacher, D., Seiler, M. V., Trautmann, H., & Grimme, C. (2022). Artificial Social Media Campaign Creation for Benchmarking and Challenging Detection Approaches. In Association, f. t. A. o. A. I. (. (Ed.), Workshop Proceedings of the 16th International Conference on Web and Social Media (ICWSM) (pp. 1–10). Palo Alto, CA, USA: AAAI Press.
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    Forschungsartikel (Zeitschrift)

    Clever, L., Pohl, J. S., Bossek, J., Kerschke, P., & Trautmann, H. (2022). Process-Oriented Stream Classification Pipeline: A Literature Review. Applied Sciences, 12(8), 1–44.
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    Heins, J., Bossek, J., Pohl, J. S., Seiler, M. V., Trautmann, H., & Kerschke, P. (2022). A Study on the Effects of Normalized TSP Features for Automated Algorithm Selection. Theoretical Computer Science (Theoret. Comput. Sci.), 940.
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    Abstract in Sammelband (Konferenz)

    Leszkiewicz, A., Bucur, D., Grimme, C., Michalski, R., Clever, L., Pohl, J. S., Rook, J., Bossek, J., Preuss, M., Squillero, G., Quer, S., Calabrese, A., Iacca, G., Kizgin, H., & Trautmann, H. (2022). Social Influence Analysis (SIA) in Online Social Networks.
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    Forschungsartikel in Online-Sammlung

    Pohl, J. S., Seiler, M. V., Assenmacher, D., & Grimme, C. (2022). A Twitter Streaming Dataset collected before and after the Onset of the War between Russia and Ukraine in 2022.
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  • 2021

    Forschungsartikel in Sammelband (Konferenz)

    Heins, J., Bossek, J., Pohl, J., Seiler, M., Trautmann, H., & Kerschke, P. (2021). On the Potential of Normalized TSP Features for Automated Algorithm Selection. In Association, f. C. M. (Ed.), Proceedings of the 16th ACM/SIGEVO Conference on Foundations of genetic Algorithms (FOGA XVI) (pp. 1–15). Dornbirn, Austria: ACM Press.
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  • 2020

    Forschungsartikel in Sammelband (Konferenz)

    Assenmacher, D., Clever, L., Pohl, J., Trautmann, H., & Grimme, C. (2020). A Two-Phase Framework for Detecting Manipulation Campaigns in Social Media. In Meiselwitz, G. (Ed.), Proceedings of the International Conference on Human-Computer Interaction (HCII 2020): Social Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis (pp. 201–214). Cham: Springer International Publishing.
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    Seiler, M. V., Pohl, J., Bossek, J., Kerschke, P., & Trautmann, H. (2020). Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. In Proceedings of the 16th International Conference on Parallel Problem Solving from Nature (PPSN XVI), Leiden, The Netherlands, 48–64.
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