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The goal of hate speech detection is to filter negative online content aiming at certain groups of people.
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Davidson, T., Warmsley, D., Macy, M., Weber, I.: Automated hate speech detection and the problem of offensive language. In: Proceedings of the 11th International AAAI Conference on Web and Social Media. ICWSM ’17, pp. 512–515 (2017)
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Waseem, Z., Chung, W.H.K., Hovy, D., Tetreault, J. (eds.): Proceedings of the First Workshop on Abusive Language Online. Association for Computational Linguistics, Vancouver, BC, Canada (2017)
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de Gibert, O., Perez, N., García-Pablos, A., Cuadros, M.: Hate speech dataset from a white supremacy forum”. In: Proceedings of the 2nd Workshop on Abusive Language Online (ALW2), pp. 11–20 (2018)
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Ruppenhofer, J., Siegel, M., Wiegand, M. (eds.): Proceedings of the GermEval 2018 Workshop. Austrian Academy of Sciences, Vienna, Austria (2018)
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Wiegand, M., Siegel, M., Ruppenhofer, J.: Overview of the germeval 2018 shared task on the identification of offensive language. In: Proceedings of GermEval 2018, 14th Conference on Natural Language Processing (KONVENS 2018), pp. 1–10 (2018)
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Fišer, D., Huang, R., Prabhakaran, V., Voigt, R., Waseem, Z., Wernimont, J. (eds.): Proceedings of the 2nd Workshop on Abusive Language Online (ALW2). Association for Computational Linguistics, Brussels, Belgium (2018)
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Majumder, P., Patel, D., Modha, S., Mandl, T.: Overview of the HASOC track at FIRE 2019: Hate Speech and Offensive Content Identification in Indo-European Languages. In: Proceedings of the 11th Forum for Information Retrieval Evaluation, pp. 14–17 (2019)
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Roberts, S.T., Tetreault, J., Prabhakaran, V., Waseem, Z. (eds.): Proceedings of the Third Workshop on Abusive Language Online. Association for Computational Linguistics, Florence, Italy (2019)
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Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 4171–4186 (2019). https://www.aclweb.org/anthology/N19-1423.pdf
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Xi, J., Spranger, M., Labudde, D.: CNN-Based Offensive Language Detection. In: Proceedings of the GermEval 2018 Workshop (2018)
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Wiedemann, G., Ruppert, E., Jindal, R., Biemann, C.: Transfer Learning from LDA to BiLSTM-CNN for Offensive Language Detection in Twitter. In: Proceedings of the GermEval 2018 Workshop (2018)
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Artetxe, M., Labaka, G., Agirre, E.: A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, pp. 789–798 (2018). https://www.aclweb.org/anthology/P18-1073/
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Wiegand, M., Amann, A., Anikina, T., Azoidou, A., Borisenkov, A., Kolmorgen, K., Kröger, I., Schäfer, C.: Saarland University’s Participation in the GermEval Task 2018 (UdSW) - Examining Different Types of Classifiers and Features. In: Proceedings of the GermEval 2018 Workshop, pp. 21–26 (2018)
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Mathur, P., Sawhney, R., Ayyar, M., Shah, R.: Did you offend me? classification of offensive tweets in Hinglish language. In: Proceedings of the 2nd Workshop on Abusive Language Online (ALW2), pp. 138–148. Association for Computational Linguistics, Brussels, Belgium (2018)
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De Smedt, T., Jaki, S.: Challenges of Automatically Detecting Offensive Language Online: Participation Paper for the Germeval Shared Task 2018 (HaUA). In: Proceedings of the GermEval 2018 Workshop, pp. 27–32 (2018)
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2019
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Johnson, J., Khoshgoftaar, T.: Survey on deep learning with class imbalance. Journal of Big Data 6
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Vidgen, B., Derczynski, L.: Directions in abusive language training data, a systematic review: Garbage in, garbage out. PLOS ONE 15
2020
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Fortuna, P., Soler, J., Wanner, L.: Toxic, hateful, offensive or abusive? what are we really classifying? an empirical analysis of hate speech datasets. In: Proceedings of the 12th Language Resources and Evaluation Conference, pp. 6786–6794. European Language Resources Association, Marseille, France (2020). https://aclanthology.org/2020.lrec-1.838
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Ranasinghe, T., Zampieri, M.: Multilingual offensive language identification with cross-lingual embeddings. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 5838–5844 (2020). https://www.aclweb.org/anthology/2020.emnlp-main.470
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Stappen, L., Brunn, F., Schuller, B.: Cross-lingual Zero- and Few-shot Hate Speech Detection Utilising Frozen Transformer Language Models and AXEL (2020)
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Mohammed, R., Rawashdeh, J., Abdullah, M.: Machine learning with oversampling and undersampling techniques: Overview study and experimental results. (2020)
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Madukwe, K., Gao, X., Xue, B.: In data we trust: A critical analysis of hate speech detection datasets. In: Proceedings of the Fourth Workshop on Online Abuse and Harms, pp. 150–161. Association for Computational Linguistics, Online (2020). https://www.aclweb.org/anthology/2020.alw-1.18
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Bigoulaeva, I., Hangya, V., Fraser, A.: Cross-lingual transfer learning for hate speech detection. In: Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion, pp. 15–25. Association for Computational Linguistics, Kyiv (2021)
2021
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