S. Agrawal and A. Awekar, Deep learning for detecting cyberbullying across multiple social media platforms, ECIR, pp.141-153, 2018.

P. Arslan, M. Corazza, E. Cabrio, and S. Villata, Overwhelmed by Negative Emotions?, Maybe You Are Being Cyber-bullied! In Proceedings of the 34th ACM/SIGAPP Symposium On Applied Computing (SAC), 2019.
URL : https://hal.archives-ouvertes.fr/hal-02020829

V. Basile, C. Bosco, E. Fersini, D. Nozza, V. Patti et al., SemEval-2019 task 5: Multilingual detection of hate speech against immigrants and women in twitter, Proceedings of the 13th International Workshop on Semantic Evaluation, pp.54-63, 2019.

C. Bosco, F. Dell'orletta, F. Poletto, M. Sanguinetti, and M. Tesconi, Overview of the EVALITA 2018 hate speech detection task, Proceedings of, 2018.

M. Carmona, E. Guzmán-falcón, M. Montes-y-gómez, H. J. Escalante, L. V. Pineda et al., Overview of MEX-A3T at IberEval 2018: Authorship and Aggressiveness Analysis in Mexican Spanish Tweets, Proceedings of IberEval 2018, pp.74-96, 2018.

C. Casula, A. Palmero-aprosio, S. Menini, and S. Tonelli, , 2020.

, Using Multi-channel BERT for Multilingual Offensive Language Detection, Proceedings of the 13th International Workshop on Semantic Evaluation (SemEval-2020), vol.12

A. Conneau and G. Lample, Crosslingual language model pretraining, Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems, pp.7057-7067, 2019.

M. Corazza, S. Menini, P. Arslan, R. Sprugnoli, E. Cabrio et al., Comparing different supervised approaches to hate speech detection, Proceedings of the Sixth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop (EVALITA 2018) co-located with the Fifth Italian Conference on Computational Linguistics, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01920266

M. Corazza, S. Menini, E. Cabrio, S. Tonelli, and S. Villata, A multilingual evaluation for online hate speech detection, ACM Transactions on Internet Technology (TOIT), vol.20, issue.2, pp.1-22, 2020.
URL : https://hal.archives-ouvertes.fr/hal-02972184

J. Devlin, M. Chang, K. Lee, and K. Toutanova, BERT: Pre-training of deep bidirectional transformers for language understanding, Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, vol.1, pp.4171-4186, 2019.

D. Fi?er, R. Huang, V. Prabhakaran, and R. Voigt, Zeerak Waseem, and Jacqueline Wernimont, editors, Proceedings of the 2nd Workshop on Abusive Language Online (ALW2). Association for Computational Linguistics, 2018.

P. Fortuna and S. Nunes, A survey on automatic detection of hate speech in text, ACM Comput. Surv, vol.51, issue.4, 2018.

A. Founta, C. Djouvas, D. Chatzakou, I. Leontiadis, J. Blackburn et al., Large scale crowdsourcing and characterization of twitter abusive behavior, ICWSM, pp.491-500, 2018.

P. Koehn, H. Hoang, A. Birch, C. Callison-burch, M. Federico et al., Moses: Open source toolkit for statistical machine translation, ACL: demo and poster, pp.177-180, 2007.

Y. Lee, S. Yoon, and K. Jung, Comparative studies of detecting abusive language on twitter, 2018.

Y. Liu, M. Ott, N. Goyal, J. Du, M. Joshi et al., Roberta: A robustly optimized BERT pretraining approach, 2019.

X. Lu, W. Ai, X. Liu, Q. Li, N. Wang et al., Learning from the ubiquitous language: An empirical analysis of emoji usage of smartphone users, UbiComp, pp.770-780, 2016.

C. Nobata, J. R. Tetreault, A. Thomas, Y. Mehdad, and Y. Chang, Abusive language detection in online user content, WWW, pp.145-153, 2016.

N. Ousidhoum, Z. Lin, H. Zhang, Y. Song, and D. Yeung, Multilingual and multi-aspect hate speech analysis, Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pp.4667-4676, 2019.

W. Endang, V. Pamungkas, and . Patti, Cross-domain and cross-lingual abusive language detection: A hybrid approach with deep learning and a multilingual lexicon, Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, vol.2, pp.363-370, 2019.

J. Ho, P. , and P. Fung, One-step and twostep classification for abusive language detection on twitter, Workshop on Abusive Language Online, pp.41-45, 2017.

F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion et al., Scikit-learn: Machine learning in Python, Journal of Machine Learning Research, vol.12, pp.2825-2830, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00650905

S. T. Roberts and J. Tetreault, Vinodkumar Prabhakaran, and Zeerak Waseem, Proceedings of the Third Workshop on Abusive Language Online. Association for Computational Linguistics, 2019.

T. Scheffler, A german twitter snapshot, Proceedings of Language Resources and Evaluation Conference (LREC), 2014.

A. Schmidt and M. Wiegand, A survey on hate speech detection using natural language processing, Proceedings of the Fifth International Workshop on Natural Language Processing for Social Media, pp.1-10, 2017.

R. Sennrich, B. Haddow, and A. Birch, Neural machine translation of rare words with subword units, ACL, 2016.

H. Sohn and H. Lee, MC-BERT4HATE: hate speech detection using multichannel BERT for different languages and translations, 2019 International Conference on Data Mining Workshops, ICDM Workshops, pp.551-559, 2019.

L. Stappen, F. Brunn, and B. W. Schuller, Cross-lingual zero-and few-shot hate speech detection utilising frozen transformer language models and AXEL. CoRR, abs, 2004.

W. L. Taylor, Cloze Procedure: A New Tool for Measuring Readability, vol.30, pp.415-433, 1953.

, Proceedings of the First Workshop on Abusive Language Online. Association for Computational Linguistics

Z. Waseem and D. Hovy, Hateful symbols or hateful people? predictive features for hate speech detection on twitter, SRW@HLT-NAACL, 2016.

M. Wiegand, J. Ruppenhofer, and T. Kleinbauer, Detection of Abusive Language: the Problem of Biased Datasets, Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, vol.1, pp.602-608, 2019.

M. Wiegand, M. Siegel, and J. Ruppenhofer, Overview of the germeval 2018 shared task on the identification of offensive language, GermEval, 2018.

E. Wulczyn, N. Thain, and L. Dixon, Ex machina: Personal attacks seen at scale, Proceedings of WWW Conference, pp.1391-1399, 2017.

D. Yin, Z. Xue, L. Hong, B. D. Davison, A. Kontostathis et al., Detection of harassment on web 2.0. In Proceedings of the Content Analysis in the Web, pp.1-7, 2009.

M. Zampieri, S. Malmasi, P. Nakov, S. Rosenthal, N. Farra et al., Predicting the type and target of offensive posts in social media, Proceedings of NAACL-HLT, 2019.

M. Zampieri, S. Malmasi, P. Nakov, S. Rosenthal, N. Farra et al., Semeval-2019 task 6: Identifying and categorizing offensive language in social media (offenseval), Proceedings of the 13th International Workshop on Semantic Evaluation, pp.75-86, 2019.

M. Zampieri, P. Nakov, S. Rosenthal, P. Atanasova, G. Karadzhov et al., Zeses Pitenis, and Ç agr? Çöltekin. 2020. SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (Offen-sEval 2020), Proceedings of SemEval

R. D. Zhang, Z. , and J. Tepper, Detecting hate speech on twitter using a convolution-gru based deep neural network, ESWC, pp.745-760, 2018.