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Text moderation for user generated content, which helps to promote healthy interaction among users, has been widely studied and many machine learning models have been proposed.
Neural word decomposition models for abusive language detection
Sravan Babu Bodapati, Spandana Gella, Kasturi Bhattacharjee, and Yaser Al-Onaizan. 2019 · 1910
Earlier work this paper cites.
Latent dirichlet allocation
David M Blei, Andrew Y Ng, and Michael I Jordan. 2003 · 2003
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Beta regression for modelling rates and proportions
Silvia Ferrari and Francisco Cribari-Neto. 2004 · 2004
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Detecting offensive language in social media to protect adolescent online safety
Ying Chen, Yilu Zhou, Sencun Zhu, and Heng Xu. 2012 · 2012
Earlier work this paper cites.
Baselines and bigrams: Simple, good sentiment and topic classification
Sida I Wang and Christopher D Manning. 2012 · 2012
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Detecting hate speech on the world wide web
William Warner and Julia Hirschberg. 2012 · 2012
Earlier work this paper cites.
Deep inside convolutional networks: Visualising image classification models and saliency maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman. 2013 · 2013
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2015 · 2015
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Abusive language detection in online user content
Chikashi Nobata, Joel Tetreault, Achint Thomas, Yashar Mehdad, and Yi Chang. 2016 · 2016
Cited alongside, same era.
Deep learning for hate speech detection in tweets
Pinkesh Badjatiya, Shashank Gupta, Manish Gupta, and Vasudeva Varma. 2017 · 2017
Cited alongside, same era.
Deeper attention to abusive user content moderation
John Pavlopoulos, Prodromos Malakasiotis, and Ion Androutsopoulos. 2017 · 2017
Cited alongside, same era.
Learning important features through propagating activation differences
Avanti Shrikumar, Peyton Greenside, and Anshul Kundaje. 2017 · 2017
Cited alongside, same era.
Deep learning for detecting cyberbullying across multiple social media platforms
Sweta Agrawal and Amit Awekar. 2018 · 2018
Cited alongside, same era.
Classification of semantic paraphasias: Optimization of a word embedding model
Katy McKinney-Bock and Steven Bedrick. 2019 · 2019
Later among the works it cites.
How to fine-tune bert for text classification?
Chi Sun, Xipeng Qiu, Yige Xu, and Xuanjing Huang. 2019 · 2019
Later among the works it cites.
Exploration of gender differences in covid-19 discourse on reddit
Jai Aggarwal, Ella Rabinovich, and Suzanne Stevenson. 2020 · 2020
Later among the works it cites.
Development of multi-level linguistic alignment in child-adult conversations
Thomas Misiek, Benoit Favre, and Abdellah Fourtassi. 2020 · 2020
Later among the works it cites.
Toxicity detection: Does context really matter?
John Pavlopoulos, Jeffrey Sorensen, Lucas Dixon, Nithum Thain, and Ion Androutsopoulos. 2020 · 2020
Later among the works it cites.
Tnt: Text normalization based pre-training of transformers for content moderation
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David Noever. 2018 · 2018
Cited alongside, same era.
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.
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.
https://en.wikipedia.org/wiki/Beta_distribution
Wiki Distribution Beta
Cited in the paper.
https://www.perspectiveapi.com
Google Perspectiveapi
Cited in the paper.
Fei Tan, Yifan Hu, Changwei Hu, Keqian Li, and Kevin Yen. 2020 · 2020
Later among the works it cites.
Habertor: An efficient and effective deep hatespeech detector
Thanh Tran, Yifan Hu, Changwei Hu, Kevin Yen, Fei Tan, Kyumin Lee, and Se Rim Park. 2020 · 2020
Later among the works it cites.