Fetching the paper…
Reading the bibliography…
Automatic hate speech detection is hampered by the scarcity of labeled datasetd, leading to poor generalization.
UTFPR at semeval-2019 task 5: Hate speech identification with recurrent neural networks
Gustavo Henrique Paetzold, Shervin Malmasi, and Marcos Zampieri. 2019 · 1904
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Hatebert: Retraining BERT for abusive language detection in english
Tommaso Caselli, Valerio Basile, Jelena Mitrovic, and Michael Granitzer. 2020 · 2010
Earlier work this paper cites.
Hateful symbols or hateful people? predictive features for hate speech detection on twitter
Zeerak Waseem and Dirk Hovy. 2016 · 2016
Earlier work this paper cites.
Automated hate speech detection and the problem of offensive language
Thomas Davidson, Dana Warmsley, Michael Macy, and Ingmar Weber. 2017 · 2017
Earlier work this paper cites.
Hate speech dataset from a white supremacy forum
Ona de Gibert, Naiara Perez, Aitor García-Pablos, and Montse Cuadros. 2018 · 2018
Earlier work this paper cites.
A survey on automatic detection of hate speech in text
Paula Fortuna and Sérgio Nunes. 2018 · 2018
Earlier work this paper cites.
Large scale crowdsourcing and characterization of twitter abusive behavior
Antigoni Maria Founta, Constantinos Djouvas, Despoina Chatzakou, Ilias Leontiadis, Jeremy Blackburn, Gianluca Stringhini, Athena Vakali, Michael Sirivianos, and Nicolas Kourtellis. 2018 · 2018
Earlier work this paper cites.
Detecting hate speech on twitter using a convolution-gru based deep neural network
Ziqi Zhang, David Robinson, and Jonathan Tepper. 2018 · 2018
Cited alongside, same era.
Semeval-2019 task 5: Multilingual detection of hate speech against immigrants and women in twitter
Valerio Basile, Cristina Bosco, Elisabetta Fersini, Debora Nozza, Viviana Patti, Francisco Manuel Rangel Pardo, Paolo Rosso, and Manuela Sanguinetti. 2019 · 2019
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Cited alongside, same era.
Augment to prevent: Short-text data augmentation in deep learning for hate-speech classification
Georgios Rizos, Konstantin Hemker, and Björn Schuller. 2019 · 2019
Cited alongside, same era.
HateGAN: Adversarial generative-based data augmentation for hate speech detection
Rui Cao and Roy Ka-Wei Lee. 2020 · 2020
Later among the works it cites.
Don’t stop pretraining: Adapt language models to domains and tasks
Suchin Gururangan, Ana Marasović, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, and Noah A. Smith. 2020 · 2020
Later among the works it cites.
Using transfer-based language models to detect hateful and offensive language online
Vebjørn Isaksen and Björn Gambäck. 2020 · 2020
Later among the works it cites.
Contextualizing hate speech classifiers with post-hoc explanation
Brendan Kennedy, Xisen Jin, Aida Mostafazadeh Davani, Morteza Dehghani, and Xiang Ren. 2020 · 2020
Later among the works it cites.
ALBERT: A lite BERT for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2020 · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Detection of abusive language: the problem of biased datasets
Michael Wiegand, Josef Ruppenhofer, and Thomas Kleinbauer. 2019 · 2019
Cited alongside, same era.
Do not have enough data? deep learning to the rescue!
Ateret Anaby-Tavor, Boaz Carmeli, Esther Goldbraich, Amir Kantor, George Kour, Segev Shlomov, Naama Tepper, and Naama Zwerdling. 2020 · 2020
Cited alongside, same era.
Balancing via generation for multi-class text classification improvement
Naama Tepper, Esther Goldbraich, Naama Zwerdling, George Kour, Ateret Anaby Tavor, and Boaz Carmeli. 2020 · 2020
Later among the works it cites.
Towards hate speech detection at large via deep generative modeling
Tomer Wullach, Amir Adler, and Einat Minkov. 2021 · 2021
Closest in time.