• 2022

    Research article (book contribution)

    Niemann, M., Assenmacher, D., Brunk, J., Riehle, D. M., Becker, J., & Trautmann, H. (2022). (Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse. In Weitzel, G., & Mündges, S. (Eds.), Hate Speech — Definitionen, Ausprägungen, Lösungen (pp. 249–274). Wiesbaden: VS Verlag für Sozialwissenschaften.
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  • 2021

    Research article (journal)

    Brunk, J., Stierle, M., Papke, L., Revoredo, K., Matzner, M., & Becker, J. (2021). Cause vs. Effect in Context-Sensitive Prediction of Business Process Instances. Information Systems, 95(1).
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    Thesis (doctoral or post-doctoral)

    Brunk, J. (2021). Prediction of Business Processes — Selection and Development of Interpretable Machine Learning-based Next Activity Prediction Techniques. at the Universität Münster. Münster: Selbstverlag — Eigenverlag.
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    Research article in digital collection (conference)

    Stierle, M., Brunk, J., Weinzierl, S., Zilker, S., Matzner, M., & Becker, J. (2021). Bringing Light Into the Darkness — A Systematic Literature Review on Explainable Predictive Business Process Monitoring Techniques.
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    Wolf, F., Brunk, J., & Becker, J. (2021). A Framework of Business Process Monitoring and Prediction Techniques.
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  • 2020

    Research article in proceedings (conference)

    Becker, J., Brunk, J., Ding, W., & Niemann, M. (2020). Conceptualization of an Integrated Procedure Model for Business Process Monitoring and Prediction. In Guédria, W., Proper, H. A., Verelst, J., Hacks, S., Timm, F., Sandkuhl, K., Fellmann, M., Serapiao, G., Payan, M., Komarov, M., Maltseva, S., Uskenbayeva, R., Nazarov, D., Ge, M., Helfert, M., & Ehrlinger, L. (Eds.), Proceeding. 2020 IEEE 22nd Conference on Business Informatics (CBI 2020). Antwerp, Belgium 22-24 June 2020. Volume 2 — Research-in-Progress and Workshop Papers (pp. 49–57). Los Alamitos, California: Wiley-IEEE Computer Society Press.
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    Brunk, J. (2020). Structuring Business Process Context Information for Process Monitoring and Prediction. In Guédria, W., Proper, H. A., Verelst, J., Hacks, S., Timm, F., Sandkuhl, K., Fellmann, M., Serapiao, G., Payan, M., Komarov, M., Maltseva, S., Uskenbayeva, R., Nazarov, D., Ge, M., Helfert, M., & Ehrlinger, L. (Eds.), Proceeding. 2020 IEEE 22nd Conference on Business Informatics (CBI 2020). Antwerp, Belgium 22-24 June 2020. Volume 2 — Research-in-Progress and Workshop Papers (pp. 39–48). Los Alamitos, California: Wiley-IEEE Computer Society Press.
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    Niemann, M., Riehle, D. M., Brunk, J., & Becker, J. (2020). What is Abusive Language? — Integrating Different Views on Abusive Language for Machine Learning. In Grimme, C., Preuss, M., Takes, F., & Waldherr, A. (Eds.), Disinformation in Open Online Media — MISDOOM 2019 (pp. 59–73). Lecture Notes in Computer Science: Vol. 12021. Springer.
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    Niemann, M., Welsing, J., Riehle, D. M., Brunk, J., Assenmacher, D., & Becker, J. (2020). Abusive Comments in Online Media and How to Fight Them: State of the Domain and a Call to Action. In van Duijn, , Max;, P., Mike;, S., Viktoria;, T., Frank;, V., & Suzan, (Eds.), Disinformation in Open Online Media. Second Multidisciplinary International Symposium, MISDOOM 2020, Leiden, The Netherlands, October 26–27, 2020, Proceedings (pp. 122–137). Lecture Notes in Computer Science: Vol. 12259. Cham: Springer.
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    Riehle, D. M., Niemann, M., Brunk, J., Assenmacher, D., Trautmann, H., & Becker, J. (2020). Building an Integrated Comment Moderation System — Towards a Semi-Automatic Moderation tool. In Meiselwitz, G. (Ed.), Social Computing and Social Media. Participation, User Experience, Consumer Experience, and Applications of Social Computing. 12th International Conference, SCSM 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings, Part II (pp. 71–86). Lecture Notes in Computer Science: Vol. 12195. Cham: Springer.
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    Weinzierl, S., Zilker, S., Brunk, J., Revoredo, K., Matzner, M., & Becker, J. (2020). XNAP: Making LSTM-based Next Activity Predictions Explainable by Using LRP. In Del, R. O., A.;, L., H.;, S., & F.M., (Eds.), Business Process Management Workshops. BPM 2020 International Workshops, Seville, Spain, September 13–18, 2020, Revised Selected Papers (pp. 129–141). Lecture Notes in Business Information Processing: Vol. 397. Cham: Springer.
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    Research article (journal)

    Brunk, J., Stottmeister, J., Weinzierl, S., Matzner, M., & Becker, J. (2020). Exploring the Effect of Context Information on Deep Learning Business Process Predictions. Journal of Decision Systems, 29(sup1), 328–343.
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    Research article in digital collection (conference)

    Brunk, J., Methner, C., Cordes, A.-K., Thiermann, S., & Goerke, T. (2020). Trace Clustering for an Online Freight Exchange at TIMOCOM.
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    Jorgensen, M., Choi, M., Niemann, M., Brunk, J., & Becker, J. (2020). Multi-Class Detection of Abusive Language Using Automated Machine Learning.
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  • 2019

    Abstract in Online-Sammlung (Konferenz)

    Niemann, M., Riehle, D. M., Brunk, J., & Becker, J. (2019). What is Abusive Language? — Integrating Different Views on Abusive Language for Machine Learning. Poster session presented at the Multidisciplinary International Symposium on Disinformation in Open Online Media, Hamburg, Germany.
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    Research article in digital collection (conference)

    Brunk, J., Mattern, J., & Riehle, D. M. (2019). Effect of Transparency and Trust on Acceptance of Automatic Online Comment Moderation Systems.
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    Brunk, J., Niemann, M., & Riehle, D. M. (2019). Can Analytics as a Service Save the Online Discussion Culture? — The Case of Comment Moderation in the Media Industry.
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  • 2018

    Research article in proceedings (conference)

    Brunk, J., Revoredo, K., Stierle, M., Matzner, M., Delfmann, P., & Becker, J. (2018). Prediction of Business Process Instances with Dynamic Bayesian Networks. In Ceravolo, P., Gómez, L. M. T., & Van, K. M. (Eds.), Proceedings of the 8th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2018) (pp. 50–54). Sevilla, Spanien: CEUR Workshop Proceedings.
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    Brunk, J., Riehle, D. M., & Delfmann, P. (2018). Prediction of Customer Movements in Large Tourism Industries by the Means of Process Mining. In Proceedings of the European Conference on Information Systems (ECIS 2018), Portsmouth, UK.
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  • 2017

    Research article in proceedings (conference)

    Riehle, D. M., Höhenberger, S., Brunk, J., Delfmann, P., & Becker, J. (2017). [εm] — Process Analysis using a Meta Modeling Tool. In Proceedings of the Conceptual Modeling Demos (ER Demos 2017), Valencia, Spain, 334–337.
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  • 2014

    Working paper

    Riemer, K., Gal, U., Brunk, J., Gilchriest, B., Ord, R., & Tong, J.-A. (2014). Australian Digital Commerce: Now is the Time for Australian Retailers to Address the Customer Engagement Gap. In Australian Digital Transformation Lab: Vol. 2. Sydney, Australia.
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  • 2013

    Working paper

    Riemer, K., Brunk, J., Gal, U., Gilchriest, B., & Ord, R. (2013). Australian Digital Commerce: A commentary on the retail sector. In Australian Digital Transformation Lab: Vol. 1. Sydney, Australia.
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