Hate Speech Detection

Hate speech detection is the task of detecting if communication such as text, audio, and so on contains hatred and or encourages violence towards a person or a group of people. This is usually based on prejudice against 'protected characteristics' such as their ethnicity, gender, sexual orientation, religion, age et al. Some example benchmarks are ETHOS and HateXplain. Models can be evaluated with metrics like the F-score or F-measure.

Papers

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Showing 421–430 of 507 papers

Title	Date	Tasks	Status
To BAN or not to BAN: Bayesian Attention Networks for Reliable Hate Speech Detection	Jul 10, 2020	ClassificationGeneral Classification	—Unverified
Automatic Detection of Sexist Statements Commonly Used at the Workplace	Jul 8, 2020	Hate Speech DetectionSentiment Analysis	CodeCode Available
TweetBLM: A Hate Speech Dataset and Analysis of Black Lives Matter-related Microblogs on Twitter:	Jun 25, 2020	Hate Speech Detection	—Unverified
SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)	Jun 12, 2020	Abusive LanguageHate Speech Detection	—Unverified
Investigating Deep Learning Approaches for Hate Speech Detection in Social Media	May 29, 2020	Hate Speech Detection	—Unverified
Demoting Racial Bias in Hate Speech Detection	May 25, 2020	Hate Speech Detection	—Unverified
Leveraging Affective Bidirectional Transformers for Offensive Language Detection	May 16, 2020	Data AugmentationFeature Engineering	—Unverified
OSACT4 Shared Task on Offensive Language Detection: Intensive Preprocessing-Based Approach	May 14, 2020	ClassificationDimensionality Reduction	—Unverified
Towards Hate Speech Detection at Large via Deep Generative Modeling	May 13, 2020	DiversityHate Speech Detection	CodeCode Available
Code-switching patterns can be an effective route to improve performance of downstream NLP applications: A case study of humour, sarcasm and hate speech detection	May 5, 2020	Hate Speech Detection	—Unverified

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All datasets Ethos Binary HateXplain Ethos MultiLabel Waseem et al., 2018 AbusEval Automatic Misogynistic Identification HateMM HatEval OffensEval 2019 ToLD-Br bajer_danish_misogyny DKhate

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	BiLSTM + static BE	F1-score	0.8	—	Unverified
2	BERT	F1-score	0.79	—	Unverified
3	BiLSTM+Attention+FT	F1-score	0.77	—	Unverified
4	OPT-175B (few-shot)	F1-score	0.76	—	Unverified
5	CNN+Attention+FT+GV	F1-score	0.74	—	Unverified
6	OPT-175B (one-shot)	F1-score	0.71	—	Unverified
7	OPT-175B (zero-shot)	F1-score	0.67	—	Unverified
8	SVM	F1-score	0.66	—	Unverified
9	Random Forests	F1-score	0.64	—	Unverified
10	Davinci (zero-shot)	F1-score	0.63	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BERT-MRP	AUROC	0.86	—	Unverified
2	BERT-RP	AUROC	0.85	—	Unverified
3	BERT-HateXplain [LIME]	AUROC	0.85	—	Unverified
4	BERT-HateXplain [Attn]	AUROC	0.85	—	Unverified
5	BERT [Attn]	AUROC	0.84	—	Unverified
6	BiRNN-HateXplain [Attn]	AUROC	0.81	—	Unverified
7	BiRNN-Attn [Attn]	AUROC	0.8	—	Unverified
8	CNN-GRU [LIME]	AUROC	0.79	—	Unverified
9	BiRNN [LIME]	AUROC	0.77	—	Unverified
10	XG-HSI-BERT	Accuracy	0.75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MLARAM	Hamming Loss	0.29	—	Unverified
2	MLkNN	Hamming Loss	0.16	—	Unverified
3	Binary Relevance	Hamming Loss	0.14	—	Unverified
4	Neural Classifier Chains	Hamming Loss	0.13	—	Unverified
5	Neural Binary Relevance	Hamming Loss	0.11	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Mozafari et al., 2019	AAA	50.94	—	Unverified
2	SVM	AAA	46.51	—	Unverified
3	Kennedy et al., 2020	AAA	45.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HateBERT	Macro F1	0.74	—	Unverified
2	BERT	Macro F1	0.72	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	mBert	Accuracy	0.83	—	Unverified
2	Logistic Regression	Accuracy	0.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HXP + CLAP + CLIP	TEST F1 (macro)	0.85	—	Unverified
2	BERT + ViT + MFCC	TEST F1 (macro)	0.79	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HateBERT	Macro F1	0.49	—	Unverified
2	BERT	Macro F1	0.48	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HateBERT	Macro F1	0.81	—	Unverified
2	BERT	Macro F1	0.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Multilingual BERT	F1-score	0.75	—	Unverified
2	AutoML	F1-score	0.74	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	AOM mBERT	F1	0.85	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Baseline	F1	0.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBERTa-large-ST	Macro F1	80.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Baseline BERT (task A)	F1	0.77	—	Unverified