A survey on hate speech detection using natural language processing A Schmidt, M Wiegand Proceedings of the Fifth International Workshop on Natural Language …, 2019 | 1564 | 2019 |
A survey on the role of negation in sentiment analysis M Wiegand, A Balahur, B Roth, D Klakow, A Montoyo Proceedings of the workshop on negation and speculation in natural language …, 2010 | 379 | 2010 |
Overview of the GermEval 2018 Shared Task on the Identification of Offensive Language M Wiegand, M Siegel, J Ruppenhofer 14th Conference on Natural Language Processing KONVENS 2018, 2018 | 361 | 2018 |
Detection of Abusive Language: the Problem of Biased Datasets M Wiegand, J Ruppenhofer, T Kleinbauer Proceedings of the 2019 Conference of the North American Chapter of the …, 2019 | 289 | 2019 |
Inducing a Lexicon of Abusive Words–a Feature-Based Approach M Wiegand, J Ruppenhofer, A Schmidt, C Greenberg Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 186 | 2018 |
Overview of GermEval Task 2, 2019 shared task on the identification of offensive language JM Struß, M Siegel, J Ruppenhofer, M Wiegand, M Klenner | 121 | 2019 |
A survey of noise reduction methods for distant supervision B Roth, T Barth, M Wiegand, D Klakow Proceedings of the 2013 workshop on Automated knowledge base construction, 73-78, 2013 | 79 | 2013 |
Overview of the clef–2022 checkthat! lab on fighting the covid-19 infodemic and fake news detection P Nakov, A Barrón-Cedeño, G da San Martino, F Alam, JM Struß, T Mandl, ... International Conference of the Cross-Language Evaluation Forum for European …, 2022 | 78 | 2022 |
Overview of the GermEval 2021 shared task on the identification of toxic, engaging, and fact-claiming comments J Risch, A Stoll, L Wilms, M Wiegand Proceedings of the GermEval 2021 Shared Task on the Identification of Toxic …, 2021 | 68 | 2021 |
Implicitly Abusive Language–What does it actually look like and why are we not getting there? M Wiegand, J Ruppenhofer, E Eder Proceedings of the 2021 Conference of the North American Chapter of the …, 2021 | 68 | 2021 |
Effective slot filling based on shallow distant supervision methods B Roth, T Barth, M Wiegand, M Singh, D Klakow arXiv preprint arXiv:1401.1158, 2014 | 64 | 2014 |
Convolution kernels for opinion holder extraction M Wiegand, D Klakow Human Language Technologies: The 2010 Annual Conference of the North …, 2010 | 63 | 2010 |
MLSA-A Multi-layered Reference Corpus for German Sentiment Analysis. S Clematide, S Gindl, M Klenner, S Petrakis, R Remus, J Ruppenhofer, ... LREC, 3551-3556, 2012 | 49 | 2012 |
Overview of the CLEF-2022 CheckThat! Lab: Task 3 on Fake News Detection. J Köhler, GK Shahi, JM Struß, M Wiegand, M Siegel, T Mandl, M Schütz CLEF (Working Notes), 404-421, 2022 | 40 | 2022 |
Comparing methods for deriving intensity scores for adjectives J Ruppenhofer, M Wiegand, J Brandes Proceedings of the 14th Conference of the European Chapter of the …, 2014 | 33 | 2014 |
The alyssa system at trec qa 2007: Do we need blog06? D Shen, M Wiegand, A Merkel, S Kazalski, S Hunsicker, JL Leidner, ... TREC 3, 1.2, 2007 | 28 | 2007 |
Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features M Schulder, M Wiegand, J Ruppenhofer, B Roth Proceedings of the Eighth International Joint Conference on Natural Language …, 2017 | 26 | 2017 |
Generalization methods for in-domain and cross-domain opinion holder extraction M Wiegand, D Klakow Proceedings of the 13th Conference of the European Chapter of the …, 2012 | 22 | 2012 |
A Gold Standard for Relation Extraction in the Food Domain. M Wiegand, B Roth, E Lasarcyk, S Köser, D Klakow LREC, 507-514, 2012 | 21 | 2012 |
Implicitly Abusive Comparisons–A New Dataset and Linguistic Analysis M Wiegand, M Geulig, J Ruppenhofer Proceedings of the 16th Conference of the European Chapter of the …, 2021 | 19 | 2021 |