Hi, I research online harms in the context of NLP. In my PhD I work on the detection and analysis of hateful language online. I am also passionate about analyzing values and biases in LLMs, which I do as part of the project Investigating AI's View of the World and Humanity in Religious and Social Conflicts.
My main website is located here: https://jagol.github.io/.
Education
- August 2021 - now: PhD student at the Department of Computational Linguistics
- 2019 - 2021: MA in Computational Linguistics and Language Technology (90) and Philosophy (30) at the University of Zurich
- 2015 - 2019: BA in Computational Linguistics and Language Technology (90), Philosophy (60) and General Linguistics (30) at the University of Zurich
ZORA Publikationsliste
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Publikationen
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Detecting and Mapping Hate in Religious Contexts In T. Schlag & K. Yadav (Eds.), Religious Communication, Interaction and Transformation in a Culture of Digitality : Insights into the Zurich University Research Priority Program “Digital Religion(s)” (pp. 153–183). De Gruyter. https://doi.org/10.1515/9783111721729
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The ‘Spiritual’ and the ‘Religious’ in the Twittersphere: A Topic Model and Semantic Map Journal of Religion, Media & Digital Culture, 14, 1–22. https://doi.org/10.1163/21659214-bja10123
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A Disaggregated Dataset on English Offensiveness Containing Spans (G. Abercrombie, V. Basile, S. FRENDA, S. Tonelli, & S. Dudy, Eds.; pp. 1–14–14). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.nlperspectives-1.1
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Improving Adversarial Data Collection by Supporting Annotators: Lessons from GAHD, a German Hate Speech Dataset 4405–4424. https://doi.org/10.18653/v1/2024.naacl-long.248
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AustroTox: A Dataset for Target-Based Austrian German Offensive Language Detection 11990–12001. https://doi.org/10.18653/v1/2024.findings-acl.713
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Evaluating the Effectiveness of Natural Language Inference for Hate Speech Detection in Languages with Limited Labeled Data 187–201. https://doi.org/10.18653/v1/2023.woah-1.19
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CL-UZH at SemEval-2023 Task 10: Sexism Detection through Incremental Fine-Tuning and Multi-Task Learning with Label Descriptions 1562–1572. https://doi.org/10.18653/v1/2023.semeval-1.216
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Hypothesis Engineering for Zero-Shot Hate Speech Detection 75–90. https://aclanthology.org/2022.trac-1.10
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Ranking Georeferences for Efficient Crowdsourcing of Toponym Annotations in a Historical Corpus of Alpine Texts CEUR Workshop Proceedings, online. http://ceur-ws.org/Vol-2624/paper11.pdf
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Geotagging a diachronic corpus of alpine texts: comparing distinct approaches to toponym recognition 11–18. https://doi.org/10.26615/978-954-452-059-5_003