%0 Conference Proceedings %T TUW-Inf at GermEval2021: Rule-based and Hybrid Methods for Detecting Toxic, Engaging, and Fact-Claiming Comments %A Gémes, Kinga %A Recski, Gábor %Y Risch, Julian %Y Stoll, Anke %Y Wilms, Lena %Y Wiegand, Michael %S Proceedings of the GermEval 2021 Shared Task on the Identification of Toxic, Engaging, and Fact-Claiming Comments %D 2021 %8 September %I Association for Computational Linguistics %C Duesseldorf, Germany %F gemes-recski-2021-tuw %X This paper describes our methods submitted for the GermEval 2021 shared task on identifying toxic, engaging and fact-claiming comments in social media texts (Risch et al., 2021). We explore simple strategies for semi-automatic generation of rule-based systems with high precision and low recall, and use them to achieve slight overall improvements over a standard BERT-based classifier. %U https://aclanthology.org/2021.germeval-1.10 %P 69-75