Matthias Orlikowski

Research in Natural Language Processing & Computational Social Science

I am a PhD student in the Semantic Computing Group at Bielefeld University (Germany). I work on systems to analyse and support online conversations on political topics as part of the Bots Building Bridges project. From April to June 2022 I visited the MilaNLP Lab at Bocconi University (Italy) to work on related problems in modelling socio-demographics for subjective tasks.

I have an interdisciplinary background in Sociology, Computer Science and Computational Linguistics. Before joining the Semantic Computing Group, I was an NLP solutions engineer and researcher (Prêt-à-LLOD) at AI startup Semalytix (11/2018 - 06/2021). Right after graduating, I had joined the Chair of Digital Humanities at Paderborn University (Germany) as research assistant for a couple of months (04/2018 - 08/2018). During my Masters, I spent a while (02/2017 – 04/2017) as a research intern at the Ubiquitous Knowledge Processing (UKP) Lab at TU Darmstadt (Germany).

If you are interested in exchange or collaboration on one of the mentioned topics, please don't hesitate to get in touch via Twitter or email (firstname at orlikow.ski).

Publications

2020

• Jorge Gracia, Christian Fäth, Matthias Hartung, Maxim Ionov, Julia Bosque-Gil, Susana Veríssimo, Christian Chiarcos, and Matthias Orlikowski. Leveraging Linguistic Linked Data for Cross-lingual Model Transfer in the Pharmaceutical Domain. ISWC 2020
• Thierry Declerck, John Philip McCrae, Matthias Hartung, Jorge Gracia, Christian Chiarcos, Elena Montiel-Ponsoda, Philipp Cimiano, Artem Revenko, Roser Saurí, Deirdre Lee, Stefania Racioppa, Jamal Abdul Nasir, Matthias Orlikowski, Marta Lanau-Coronas, Christian Fäth, Mariano Rico, Mohammad Fazleh Elahi, Maria Khvalchik, Meritxell Gonzalez, et al. Recent Developments for the Linguistic Linked Open Data Infrastructure. LREC 2020.

2019

• Fabian Hommel, Philipp Cimiano, Matthias Orlikowski, and Matthias Hartung. Extending Neural Question Answering with Linguistic Input Features. In Proceedings of the 5th Workshop on Semantic Deep Learning (SemDeep-5), co-located with IJCAI 2019.
• Markus Maurer, Johannes Daxenberger, Matthias Orlikowski, and Iryna Gurevych. Argument Mining: A new method for automated text analysis and its application in communication science. In Dynamische Prozesse der öffentlichen Kommunikation. Methodische Herausforderungen, Volume 15 of Methoden und Forschungslogik der Kommunikationswissenschaft. Herbert von Halem, Cologne.

2018

• Frederik Simon Bäumer, Joschka Kersting, Matthias Orlikowski, and Michaela Geierhos. Towards a Multi-Stage Approach to Detect Privacy Breaches in Physician Reviews. SEMANTiCS 2018
• Matthias Orlikowski, Matthias Hartung, and Philipp Cimiano. Learning Diachronic Analogies to Analyze Concept Change. In Proceedings of the Second Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, co-located with COLING 2018.

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