Data expansion using back translation and paraphrasing for hate speech detection

R. Cao, R.K.-W. Lee, T.-A. Hoang, DeepHate: Hate speech detection via multi-faceted text representations, in: 12th ACM Conference on Web Science, 2020, pp. 11–20. D. Cambridge, Hate speech, Cambridge Advanced Learner’s Dictionary and Thesaurus. Retrieved on 2020-12-24, https://dictionary.cambridge.org/dictionary/english/hate-speech. Wright, 2017, Cyberbullying in cultural context, J. Cross-Cultural Psychol., 48, 1136, 10.1177/0022022117723107 Kowalski, 2012 Dadvar, 2018 G. Rizos, K. Hemker, B. Schuller, Augment to prevent: Short-text data augmentation in deep learning for hate-speech classification, in: Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019, pp. 991–1000. Edunov, 2018, Understanding back-translation at scale, 489 Shen, 2019 B. Gambäck, U.K. Sikdar, Using convolutional neural networks to classify hate-speech, in: Proceedings of the First Workshop on Abusive Language Online, 2017, pp. 85–90. Poletto, 2020, Resources and benchmark corpora for hate speech detection: A systematic review, Lang. Resour. Eval., 1 Mossie, 2020, Vulnerable community identification using hate speech detection on social media, Inf. Process. Manage., 57, 10.1016/j.ipm.2019.102087 Murnion, 2018, Machine learning and semantic analysis of in-game chat for cyberbullying, Comput. Secur., 76, 197, 10.1016/j.cose.2018.02.016 A. Chakraborty, Y. Zhang, A. Ramesh, Understanding types of cyberbullying in an anonymous messaging application, in: Companion Proceedings of the the Web Conference 2018, 2018, pp. 1001–1005. Peled, 2019, Cyberbullying and its influence on academic, social, and emotional development of undergraduate students, Heliyon, 5, 10.1016/j.heliyon.2019.e01393 Chandana, 2018, Cognitive way of detecting cyberbullying in chatbots, Int. J. Adv. Res. Comput. Sci., 9, 14 Chun, 2020, An international systematic review of cyberbullying measurements, Comput. Hum. Behav., 10.1016/j.chb.2020.106485 Van Hee, 2018, Automatic detection of cyberbullying in social media text, PLoS One, 13 M. Yao, C. Chelmis, D.S. Zois, Cyberbullying ends here: Towards robust detection of cyberbullying in social media, in: The World Wide Web Conference, 2019, pp. 3427–3433. Byrne, 2018, Cyberbullying and social media: Information and interventions for school nurses working with victims, students, and families, J. Sch. Nurs., 34, 38, 10.1177/1059840517740191 D. Chatzakou, N. Kourtellis, J. Blackburn, E. De Cristofaro, G. Stringhini, A. Vakali, Mean birds: Detecting aggression and bullying on twitter, in: Proceedings of the 2017 ACM on Web Science Conference, 2017, pp. 13–22. Ducharme, 2017, SVM constraint discovery using KNN applied to the identification of cyberbullying, 111 Prathyusha, 2017, Cyberbully detection using hybrid techniques, 1 Balci, 2015, Automatic analysis and identification of verbal aggression and abusive behaviors for online social games, Comput. Hum. Behav., 53, 517, 10.1016/j.chb.2014.10.025 Foong, 2017, Cyberbullying system detection and analysis, 40 Abderrouaf, 2019, On online hate speech detection. Effects of negated data construction, 5595 Iwendi, 2020, Cyberbullying detection solutions based on deep learning architectures, Multimedia Syst., 1 A. Baruah, F. Barbhuiya, K. Dey, Abaruah at semeval-2019 task 5: Bi-directional lstm for hate speech detection, in: Proceedings of the 13th International Workshop on Semantic Evaluation, 2019, pp. 371–376. V. Indurthi, B. Syed, M. Shrivastava, N. Chakravartula, M. Gupta, V. Varma, Fermi at semeval-2019 task 5: Using sentence embeddings to identify hate speech against immigrants and women in twitter, in: Proceedings of the 13th International Workshop on Semantic Evaluation, 2019, pp. 70–74. I. Ameer, M.H.F. Siddiqui, G. Sidorov, A. Gelbukh, CIC at SemEval-2019 task 5: Simple yet very efficient approach to hate speech detection, aggressive behavior detection, and target classification in twitter, in: Proceedings of the 13th International Workshop on Semantic Evaluation, 2019, pp. 382–386. Rozental, 2019 M. Guzman-Silverio, A. Balderas-Paredes, A. López-Monroy, Transformers and data augmentation for aggressiveness detection in Mexican Spanish, in: Notebook Papers of 2nd SEPLN Workshop on Iberian Languages Evaluation Forum, IberLEF, Malaga, Spain, 2020. Wei, 2019 Xie, 2019 Jin, 2020, Is bert really robust? A strong baseline for natural language attack on text classification and entailment, vol. 34, 8018 Quteineh, 2020 A. Kumar, S. Bhattamishra, M. Bhandari, P. Talukdar, Submodular optimization-based diverse paraphrasing and its effectiveness in data augmentation, in: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1, Long and Short Papers, 2019, pp. 3609–3619. Li, 2017 Gupta, 2017 Y. Song, R. Yan, Y. Feng, Y. Zhang, D. Zhao, M. Zhang, Towards a neural conversation model with diversity net using determinantal point processes, in: Thirty-Second AAAI Conference on Artificial Intelligence, 2018. A.K. Vijayakumar, M. Cogswell, R.R. Selvaraju, Q. Sun, S. Lee, D. Crandall, D. Batra, Diverse beam search for improved description of complex scenes, in: Thirty-Second AAAI Conference on Artificial Intelligence, 2018. Ma, 2019 Vaswani, 2017, Attention is all you need, 5998 Bojar, 2018, Findings of the 2018 conference on machine translation (WMT18), 272 Sennrich, 2015 M. Ott, S. Edunov, A. Baevski, A. Fan, S. Gross, N. Ng, D. Grangier, M. Auli, fairseq: A fast, extensible toolkit for sequence modeling, in: Proceedings of NAACL-HLT 2019: Demonstrations, 2019. Kim, 2014 van Aken, 2018 Reynolds, 2011, Using machine learning to detect cyberbullying, 241 Jahan, 2020, Team oulu at semeval-2020 task 12: Multilingual identification of offensive language, type and target of twitter post using translated datasets., 10 M. Zampieri, S. Malmasi, P. Nakov, S. Rosenthal, N. Farra, R. Kumar, Predicting the type and target of offensive posts in social media, in: Proceedings of NAACL, 2019. Zampieri, 2019 W. Warner, J. Hirschberg, Detecting hate speech on the world wide web, in: Proceedings of the Second Workshop on Language in Social Media, 2012, pp. 19–26. Z. Waseem, D. Hovy, Hateful symbols or hateful people? Predictive features for hate speech detection on twitter, in: Proceedings of the NAACL Student Research Workshop, 2016, pp. 88–93. Zhang, 2016, Cyberbullying detection with a pronunciation based convolutional neural network, 740