56 Mass-Producing Language Resources by Combining Implicit Crowdsourcing and Language Learning, Proceedings of the 12th International Conference on Language Resources and Evaluation (LREC 2020), pp. 268-278, (Marseille, France, May 12-14, 2020) (poster1). (The contribution of some authors to this paper was more significant than mine. However, my contribution was more significant than others). 16. Uzan M. and HaCohen-Kerner, Y., JCT at SemEval-2020 Task 12-A: Offensive Language Detection in Tweets using Preprocessing Methods, Character and Word Ngrams (6 pages), International Workshop on Semantic Evaluation 2020, SemEval2020, December 12-13, 2020, Barcelona, Spain, collocated with The 28th International Conference on Computational Lingustics (COLING-2020). 17. Uzan M. and HaCohen-Kerner, Y., Profiling Hate Speech Spreaders on Twitter using BERT and LSTM models, accepted for publication in the Proeedings of the PAN-21, CLEF conference, Bucharest, Romania, September 21-24, 2021, electronic publishing. 18. HaCohen-Kerner, Y. and Uzan M., BIU at HASOC 2021: Detecting Offensive Language in English, Hindi, and Mahrati using Classical Supervised Machine Learning Methods and Word/Char N-grams, Accepted for publication in the Proeedings of the HASOC track at FIRE 2021: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages, Forum for Information Retrieval Evaluation, December 13-17, 2021, India, electronic publishing. 19. HaCohen-Kerner, Y., Manor, N., Bashan, N. and Dimant, E., JCT at UrduFake 2021: Detecting Fake News in URDU using Classical Supervised Machine Learning Methods and Word/Char N-grams, Accepted for publication in the Proeedings of the UrduFake track at FIRE 2021: Fake News Detection in the Urdu Language, Forum for Information Retrieval Evaluation, December 13-17, 2021, India, electronic publishing. 1 At LREC, there is no quality difference between a poster and a presentation.
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