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 121–130 of 507 papers

Title	Date	Tasks	Status
Chain-of-Translation Prompting (CoTR): A Novel Prompting Technique for Low Resource Languages	Sep 6, 2024	Hate Speech DetectionSentiment Analysis	—Unverified
Crowd-Calibrator: Can Annotator Disagreement Inform Calibration in Subjective Tasks?	Aug 26, 2024	Decision MakingHate Speech Detection	—Unverified
A Study on Bias Detection and Classification in Natural Language Processing	Aug 14, 2024	Bias DetectionHate Speech Detection	—Unverified
An Investigation Into Explainable Audio Hate Speech Detection	Aug 12, 2024	Hate Speech Detection	—Unverified
Hate Speech Detection and Classification in Amharic Text with Deep Learning	Aug 7, 2024	Deep LearningHate Speech Detection	—Unverified
LAMPO: Large Language Models as Preference Machines for Few-shot Ordinal Classification	Aug 6, 2024	Hate Speech DetectionOrdinal Classification	—Unverified
Ensemble of pre-trained language models and data augmentation for hate speech detection from Arabic tweets	Jul 2, 2024	Data AugmentationEnsemble Learning	—Unverified
A Study of Nationality Bias in Names and Perplexity using Off-the-Shelf Affect-related Tweet Classifiers	Jul 1, 2024	Bias Detectioncounterfactual	CodeCode Available
Sociocultural Considerations in Monitoring Anti-LGBTQ+ Content on Social Media	Jul 1, 2024	Hate Speech Detection	—Unverified
Watching the Watchers: A Comparative Fairness Audit of Cloud-based Content Moderation Services	Jun 20, 2024	counterfactualFairness	—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 [Attn]	AUROC	0.85	—	Unverified
4	BERT-HateXplain [LIME]	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