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In recent years, the increasing propagation of hate speech on social media and the urgent need for effective counter-measures have drawn significant investment from governments, companies, and researchers.
Hate Speech
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Guang Xiang, Bin Fan, Ling Wang, Jason Hong, and Carolyn Rose · 2012
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Efficient estimation of word representations in vector space
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Hateful symbols or hateful people? Predictive features for hate speech detection on Twitter
Zeerak Waseem and Dirk Hovy · 2013
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Jeffrey Pennington, Richard Socher, and Christopher D. Manning · 2014
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Pete Burnap and Matthew L. Williams · 2015
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Hate speech detection with comment embeddings
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Cited alongside, same era.
Countering online hate speech
Igini Galiardone, Danit Gal, Thiago Alves, and Gabriela Martinez · 2015
Cited alongside, same era.
A lexicon-based approach for hate speech detection
Njagi Dennis Gitari, Zhang Zuping, Hanyurwimfura Damien, and Jun Long · 2015
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
Cited alongside, same era.
Us and them: identifying cyber hate on twitter across multiple protected characteristics
Pete Burnap and Matthew L. Williams · 2016
Cited alongside, same era.
Intrinsic evaluation of word vectors fails to predict extrinsic performance
Billy Chiu, Anna Korhonen, and Sampo Pyysalo · 2016
Cited alongside, same era.
Automated hate speech detection and the problem of offensive language
Thoams Davidson, Dana Warmsley, Michael Macy, and Ingmar Weber · 2017
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Using convolutional neural networks to classify hate speech
Björn Gambäck and Utpal Kumar Sikdar · 2017
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Anti-muslim hate crime surges after manchester and london bridge attacks, Last accessed: July 2017, https://www.theguardian.com
Guardian · 2017
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Guardian · 2017
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Data sets: Word embeddings learned from tweets and general data
Quanzhi Li, Sameena Shah, Xiaomo Liu, and Armineh Nourbakhsh · 2017
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Do characters abuse more than words?
Yashar Mehdad and Joel Tetreault · 2016
Cited alongside, same era.
Modeling skip-grams for event detection with convolutional neural networks
Thien Huu Nguyen and Ralph Grishman · 2016
Cited alongside, same era.
Abusive language detection in online user content
Chikashi Nobata, Joel Tetreault, Achint Thomas, Yashar Mehdad, and Yi Chang · 2016
Cited alongside, same era.
Deep convolutional and LSTM recurrent neural networks for multimodal wearable activity recognition
Francisco Javier Ordóñez and Daniel Roggen · 2016
Cited alongside, same era.
Are you a racist or am i seeing things? Annotator influence on hate speech detection on Twitter
Zeerak Waseem · 2016
Cited alongside, same era.
A two phase deep learning model for identifying discrimination from tweets
Shuhan Yuan, Xintao Wu, and Yang Xiang · 2016
Cited alongside, same era.
Natasha Lomas · 2017
Later among the works it cites.
Hate on the rise after Trump’s election, Last accessed: July 2017, http://www.newyorker.com/
A. Okeowo · 2017
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One-step and two-step classification for abusive language detection on Twitter
Jo Ho Park and Pascale Fung · 2017
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‘Like sheep among wolves’: Characterizing hateful users on Twitter
Manoel Horta Ribeiro, Perod Calais, Yuri Santos, Virgilio Almeida, and Wagner Meira · 2017
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A survey on hate speech detection using natural language processing
Anna Schmidt and Michael Wiegand · 2017
Later among the works it cites.
Hate me, hate me not: Hate speech detection on Facebook
Fabio Del Vigna, Andrea Cimino, Felice Dell’Orletta, Marinella Petrocchi, and Maurizio Tesconi · 2017
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Why you should use cross-entropy error instead of classification error or mean squared error for neural network classifier training, Last accessed: Jan 2018, https://jamesmccaffrey.wordpress.com
James D. McCaffrey · 2018
Closest in time.
Hate speech detection on Twitter: feature engineering v.s. feature selection
David Robinson, Ziqi Zhang, and John Tepper · 2018
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Detecting hate speech on Twitter using a convolution-GRU based deep neural network
Ziqi Zhang, David Robinson, and John Tepper · 2018
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