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 81–90 of 507 papers

Title	Date	Tasks	Status	Score
A Benchmark Study of Contrastive Learning for Arabic Social Meaning	Oct 22, 2022	Contrastive LearningDialect Identification	CodeCode Available	5
Calibrated Learning to Defer with One-vs-All Classifiers	Feb 8, 2022	AllHate Speech Detection	CodeCode Available	5
EkoHate: Abusive Language and Hate Speech Detection for Code-switched Political Discussions on Nigerian Twitter	Apr 28, 2024	Abusive LanguageCross-Lingual Transfer	CodeCode Available	5
An Online Multilingual Hate speech Recognition System	Nov 23, 2020	Hate Speech Detectionspeech-recognition	CodeCode Available	5
Emoji-Based Transfer Learning for Sentiment Tasks	Feb 12, 2021	Hate Speech DetectionSentiment Analysis	CodeCode Available	5
Causality Guided Disentanglement for Cross-Platform Hate Speech Detection	Aug 3, 2023	DisentanglementHate Speech Detection	CodeCode Available	5
Annotating Online Misogyny	Aug 1, 2021	Abusive LanguageHate Speech Detection	CodeCode Available	5
Borrowing Human Senses: Comment-Aware Self-Training for Social Media Multimodal Classification	Mar 27, 2023	ClassificationHate Speech Detection	CodeCode Available	5
Character-level HyperNetworks for Hate Speech Detection	Nov 11, 2021	Data AugmentationHate Speech Detection	CodeCode Available	5
A Group-Specific Approach to NLP for Hate Speech Detection	Apr 21, 2023	Common Sense ReasoningEthics	CodeCode Available	5

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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