[1] Kazuki Aikawa, Shin Kawai, and Hajime Nobuhara. Multilingual inappropriate text content detection system based on doc2vec. In 2019 IEEE 8th Global Conference on Consumer Electronics (GCCE), pages 441–442. IEEE, 2019.
[2] Sai Saket Aluru, Binny Mathew, Punyajoy Saha, and Animesh Mukherjee. Deep learning models for multilingual hate speech detection. arXiv preprint arXiv:2004.06465, 2020.
[3] Mikel Artetxe and Holger Schwenk. Massively multilingual sentence embeddings for zero-shot crosslingual transfer and beyond. Transactions of the Association for Computational Linguistics, 7:597–610, 2019.
[4] Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473, 2014.
[5] Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio. Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555, 2014.
[6] Thomas Davidson, Dana Warmsley, Michael Macy, and Ingmar Weber. Automated hate speech detection and the problem of offensive language. arXiv preprint arXiv:1703.04009, 2017.
[7] Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805, 2018.
[8] Nemanja Djuric, Jing Zhou, Robin Morris, Mihajlo Grbovic, Vladan Radosavljevic, and Narayan Bhamidipati. Hate speech detection with comment embeddings. In Proceedings of the 24th international conference on world wide web, pages 29–30, 2015.
[9] Sepp Hochreiter and Jürgen Schmidhuber. Long short-term memory. Neural computation, 9(8):1735–1780, 1997.
[10] James B Jacobs. Hate crime: Criminal law and identity politics: Author’s summary. Theoretical Criminology, 6(4):481–484, 2002.
[11] Nal Kalchbrenner, Edward Grefenstette, and Phil Blunsom. A convolutional neural network for modelling sentences. arXiv preprint arXiv:1404.2188, 2014.
[12] Yoon Kim. Convolutional neural networks for sentence classification. arXiv preprint arXiv:1408.5882, 2014.
[13] Diederik P Kingma and Jimmy Ba. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980, 2014.
[14] Quoc Le and Tomas Mikolov. Distributed representations of sentences and documents. In International conference on machine learning, pages 1188–1196, 2014.
[15] Sergio Merayo-Alba, Eduardo Fidalgo, Víctor González-Castro, Rocío Alaiz-Rodríguez, and Javier Velasco-Mata. Use of natural language processing to identify inappropriate content in text. In International Conference on Hybrid Artificial Intelligence Systems, pages 254–263. Springer, 2019.
[16] Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. Distributed representations of words and phrases and their compositionality. In Advances in neural information processing systems, pages 3111–3119, 2013.
[17] Vinod Nair and Geoffrey E Hinton. Rectified linear units improve restricted boltzmann machines. In ICML, 2010.
[18] Amir H Razavi, Diana Inkpen, Sasha Uritsky, and Stan Matwin. Offensive language detection using multi-level classification. In Canadian Conference on Artificial Intelligence, pages 16–27. Springer, 2010.
[19] Hasim Sak, Andrew W Senior, and Françoise Beaufays. Long short-term memory recurrent neural network architectures for large scale acoustic modeling. 2014.
[20] Duyu Tang, Bing Qin, and Ting Liu. Document modeling with gated recurrent neural network for sentiment classification. In Proceedings of the 2015 conference on empirical methods in natural language processing, pages 1422–1432, 2015.
[21] Samuel Walker. Hate speech: The history of an American controversy. U of Nebraska Press, 1994.
[22] Yequan Wang, Minlie Huang, Xiaoyan Zhu, and Li Zhao. Attention-based lstm for aspect-level sentiment classification. In Proceedings of the 2016 conference on empirical methods in natural language processing, pages 606–615, 2016.
[23] Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, and Yoshua Bengio. Show, attend and tell: Neural image caption generation with visual attention. In International conference on machine learning, pages 2048–2057, 2015.
[24] Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V Le. Xlnet: Generalized autoregressive pretraining for language understanding. In Advances in neural information processing systems, pages 5753–5763, 2019.
[25] Harish Yenala, Ashish Jhanwar, Manoj K Chinnakotla, and Jay Goyal. Deep learning for detecting inappropriate content in text. International Journal of Data Science and Analytics, 6(4):273–286, 2018.
[26] Wen-tau Yih, Xiaodong He, and Christopher Meek. Semantic parsing for single-relation question answering. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 643–648, 2014.
[27] Shu Zhang, Dequan Zheng, Xinchen Hu, and Ming Yang. Bidirectional long short-term memory networks for relation classification. In Proceedings of the 29th Pacific Asia conference on language, information and computation, pages 73–78, 2015.
[28] Chunting Zhou, Chonglin Sun, Zhiyuan Liu, and Francis Lau. A c-lstm neural network for text classification. arXiv preprint arXiv:1511.08630, 2015.
[29] Peng Zhou, Wei Shi, Jun Tian, Zhenyu Qi, Bingchen Li, Hongwei Hao, and Bo Xu. Attention-based bidirectional long short-term memory networks for relation classification. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 207–212, 2016.