Fetching the paper…
Reading the bibliography…
Hate speech detection is complex; it relies on commonsense reasoning, knowledge of stereotypes, and an understanding of social nuance that differs from one culture to the next.
Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, R’emi Louf, Morgan Funtowicz, and Jamie Brew. 2019 · 1910
Earlier work this paper cites.
Lukas Stappen, Fabian Brunn, and Björn W. Schuller. 2020 · 2004
Earlier work this paper cites.
Ethos: an online hate speech detection dataset
Ioannis Mollas, Zoe Chrysopoulou, Stamatis Karlos, and Grigorios Tsoumakas. 2020a · 2006
Earlier work this paper cites.
Ethos: an online hate speech detection dataset
Ioannis Mollas, Zoe Chrysopoulou, Stamatis Karlos, and Grigorios Tsoumakas. 2020b · 2006
Earlier work this paper cites.
Annotating for hate speech: The maneco corpus and some input from critical discourse analysis
Stavros Assimakopoulos, Rebecca Vella Muskat, Lonneke van der Plas, and Albert Gatt. 2020a · 2008
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 W. Macy, and Ingmar Weber. 2017 · 2017
Earlier work this paper cites.
A survey on hate speech detection using natural language processing
Anna Schmidt and Michael Wiegand. 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
Cited alongside, same era.
An Italian Twitter corpus of hate speech against immigrants
Manuela Sanguinetti, Fabio Poletto, Cristina Bosco, Viviana Patti, and Marco Stranisci. 2018 · 2018
Cited alongside, same era.
Racial bias in hate speech and abusive language detection datasets
Thomas Davidson, Debasmita Bhattacharya, and Ingmar Weber. 2019 · 2019
Cited alongside, same era.
The risk of racial bias in hate speech detection
Maarten Sap, Dallas Card, Saadia Gabriel, Yejin Choi, and Noah A. Smith. 2019 · 2019
Cited alongside, same era.
Predicting the type and target of offensive posts in social media
Marcos Zampieri, Shervin Malmasi, Preslav Nakov, Sara Rosenthal, Noura Farra, and Ritesh Kumar. 2019 · 2019
Cited alongside, same era.
Hatexplain: A benchmark dataset for explainable hate speech detection
Binny Mathew, Punyajoy Saha, Seid Muhie Yimam, Chris Biemann, Pawan Goyal, and Animesh Mukherjee. 2021 · 2021
Later among the works it cites.
Stereoset: Measuring stereotypical bias in pretrained language models
Moin Nadeem, Anna Bethke, and Siva Reddy. 2021 · 2021
Later among the works it cites.
Exposing the limits of zero-shot cross-lingual hate speech detection
Debora Nozza. 2021 · 2021
Later among the works it cites.
Resources and benchmark corpora for hate speech detection: a systematic review
Fabio Poletto, Valerio Basile, Manuela Sanguinetti, Cristina Bosco, and Viviana Patti. 2021 · 2021
Later among the works it cites.
An information retrieval approach to building datasets for hate speech detection
Md Mustafizur Rahman, Dinesh Balakrishnan, Dhiraj Murthy, Mucahid Kutlu, and Matthew Lease. 2021 · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Comet-atomic 2020: On symbolic and neural commonsense knowledge graphs
Jena D. Hwang, Chandra Bhagavatula, Ronan Le Bras, Jeff Da, Keisuke Sakaguchi, Antoine Bosselut, and Yejin Choi. 2021 · 2020
Cited alongside, same era.
BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
Cited alongside, same era.
Social bias frames: Reasoning about social and power implications of language
Maarten Sap, Saadia Gabriel, Lianhui Qin, Dan Jurafsky, Noah A Smith, and Yejin Choi. 2020 · 2020
Cited alongside, same era.
Latent hatred: A benchmark for understanding implicit hate speech
Mai ElSherief, Caleb Ziems, David Muchlinski, Vaishnavi Anupindi, Jordyn Seybolt, Munmun De Choudhury, and Diyi Yang. 2021 · 2021
Cited alongside, same era.
Online hate and harassment. the american experience 2021
Anti-Defamation League. 2020 · 2021
Cited alongside, same era.
Annotating for hate speech: The MaNeCo corpus and some input from critical discourse analysis
Stavros Assimakopoulos, Rebecca Vella Muskat, Lonneke van der Plas, and Albert Gatt. 2020b
Cited in the paper.
The state of online harassment
Emily A Vogels. 2021 · 2021
Later among the works it cites.
Badr AlKhamissi and Mona T. Diab. 2022 · 2022
Closest in time.
Benchmarking post-hoc interpretability approaches for transformer-based misogyny detection
Giuseppe Attanasio, Debora Nozza, Eliana Pastor, and Dirk Hovy. 2022 · 2022
Closest in time.
Jury learning: Integrating dissenting voices into machine learning models
Mitchell L Gordon, Michelle S Lam, Joon Sung Park, Kayur Patel, Jeff Hancock, Tatsunori Hashimoto, and Michael S Bernstein. 2022 · 2022
Closest in time.
Preserving integrity in online social networks
Alon Halevy, Cristian Canton-Ferrer, Hao Ma, Umut Ozertem, Patrick Pantel, Marzieh Saeidi, Fabrizio Silvestri, and Ves Stoyanov. 2022 · 2022
Closest in time.