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 281–290 of 507 papers

Title	Date	Tasks	Status
Identifying Hate Speech Using Neural Networks and Discourse Analysis Techniques	Jun 1, 2022	Hate Speech Detection	—Unverified
Detecting Optimism in Tweets using Knowledge Distillation and Linguistic Analysis of Optimism	Jun 1, 2022	Hate Speech DetectionKnowledge Distillation	—Unverified
Deep One-Class Hate Speech Detection Model	Jun 1, 2022	BenchmarkingBinary Classification	—Unverified
Overview of OSACT5 Shared Task on Arabic Offensive Language and Hate Speech Detection	Jun 1, 2022	Hate Speech Detection	—Unverified
Beyond Explanation: A Case for Exploratory Text Visualizations of Non-Aggregated, Annotated Datasets	Jun 1, 2022	Bias DetectionHate Speech Detection	—Unverified
A Turkish Hate Speech Dataset and Detection System	Jun 1, 2022	Binary ClassificationHate Speech Detection	—Unverified
Ara-Women-Hate: An Annotated Corpus Dedicated to Hate Speech Detection against Women in the Arabic Community	Jun 1, 2022	Hate Speech Detection	—Unverified
UMUTextStats: A linguistic feature extraction tool for Spanish	Jun 1, 2022	Author ProfilingAuthorship Verification	—Unverified
Afaan Oromo Hate Speech Detection and Classification on Social Media	Jun 1, 2022	ClassificationHate Speech Detection	—Unverified
Unsupervised Embeddings with Graph Auto-Encoders for Multi-domain and Multilingual Hate Speech Detection	Jun 1, 2022	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