SOTAVerified

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 51–100 of 507 papers

TitleStatusHype
Deep Learning for Hate Speech Detection: A Comparative StudyCode1
An Effective, Robust and Fairness-aware Hate Speech Detection Framework—0
Analyzing the Real Vulnerability of Hate Speech Detection Systems against Targeted Intentional Noise—0
Accounting for Offensive Speech as a Practice of Resistance—0
A systematic review of Hate Speech automatic detection using Natural Language Processing—0
A Systematic Analysis on the Temporal Generalization of Language Models in Social Media—0
Analysis and Detection of Multilingual Hate Speech Using Transformer Based Deep Learning—0
A Survey on Hate Speech Detection using Natural Language Processing—0
A Survey on Automatic Online Hate Speech Detection in Low-Resource Languages—0
A Target-Aware Analysis of Data Augmentation for Hate Speech Detection—0
AtteSTNet -- An attention and subword tokenization based approach for code-switched text hate speech detection—0
A Turkish Hate Speech Dataset and Detection System—0
A multilingual dataset for offensive language and hate speech detection for hausa, yoruba and igbo languages—0
Afaan Oromo Hate Speech Detection and Classification on Social Media—0
Deep One-Class Hate Speech Detection Model—0
A Study on Bias Detection and Classification in Natural Language Processing—0
Adversarial Attacks and Defenses for Social Network Text Processing Applications: Techniques, Challenges and Future Research Directions—0
DeepHate: Hate Speech Detection via Multi-Faceted Text Representations—0
American Hate Crime Trends Prediction with Event Extraction—0
Assessing the impact of contextual information in hate speech detection—0
Measuring Catastrophic Forgetting in Cross-Lingual Transfer Paradigms: Exploring Tuning Strategies—0
ARGUABLY at ComMA@ICON: Detection of Multilingual Aggressive, Gender Biased, and Communally Charged Tweets Using Ensemble and Fine-Tuned IndicBERT—0
Addressing the Challenges of Cross-Lingual Hate Speech Detection—0
Data-Efficient Hate Speech Detection via Cross-Lingual Nearest Neighbor Retrieval with Limited Labeled Data—0
A Review of Challenges in Machine Learning based Automated Hate Speech Detection—0
Code-Mixed Telugu-English Hate Speech Detection—0
ARC-NLP at Multimodal Hate Speech Event Detection 2023: Multimodal Methods Boosted by Ensemble Learning, Syntactical and Entity Features—0
All You Need is "Love": Evading Hate-speech Detection—0
Data Expansion using Back Translation and Paraphrasing for Hate Speech Detection—0
Demoting Racial Bias in Hate Speech Detection—0
Ara-Women-Hate: An Annotated Corpus Dedicated to Hate Speech Detection against Women in the Arabic Community—0
CIC at SemEval-2019 Task 5: Simple Yet Very Efficient Approach to Hate Speech Detection, Aggressive Behavior Detection, and Target Classification in Twitter—0
A Dataset of Hindi-English Code-Mixed Social Media Text for Hate Speech Detection—0
Cross-lingual Zero- and Few-shot Hate Speech Detection Utilising Frozen Transformer Language Models and AXEL—0
Chain-of-Translation Prompting (CoTR): A Novel Prompting Technique for Low Resource Languages—0
Ceasing hate withMoH: Hate Speech Detection in Hindi-English Code-Switched Language—0
Cross-Platform Hate Speech Detection with Weakly Supervised Causal Disentanglement—0
Crowd-Calibrator: Can Annotator Disagreement Inform Calibration in Subjective Tasks?—0
Arabic Offensive Language Detection with Attention-based Deep Neural Networks—0
A Legal Approach to Hate Speech – Operationalizing the EU’s Legal Framework against the Expression of Hatred as an NLP Task—0
Antisemitic Messages? A Guide to High-Quality Annotation and a Labeled Dataset of Tweets—0
Class-based Prediction Errors to Detect Hate Speech with Out-of-vocabulary Words—0
Can Prompting LLMs Unlock Hate Speech Detection across Languages? A Zero-shot and Few-shot Study—0
Cross-lingual hate speech detection based on multilingual domain-specific word embeddings—0
Anti-Asian Hate Speech Detection via Data Augmented Semantic Relation Inference—0
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—0
Combating high variance in Data-Scarce Implicit Hate Speech Classification—0
Common Ground, Diverse Roots: The Difficulty of Classifying Common Examples in Spanish Varieties—0
ALT Submission for OSACT Shared Task on Offensive Language Detection—0
Cross-lingual Hate Speech Detection using Transformer Models—0
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All datasetsEthos BinaryHateXplainEthos MultiLabelWaseem et al., 2018AbusEvalAutomatic Misogynistic IdentificationHateMMHatEvalOffensEval 2019ToLD-Brbajer_danish_misogynyDKhate

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BiLSTM + static BEF1-score0.8—Unverified
2BERTF1-score0.79—Unverified
3BiLSTM+Attention+FTF1-score0.77—Unverified
4OPT-175B (few-shot)F1-score0.76—Unverified
5CNN+Attention+FT+GVF1-score0.74—Unverified
6OPT-175B (one-shot)F1-score0.71—Unverified
7OPT-175B (zero-shot)F1-score0.67—Unverified
8SVMF1-score0.66—Unverified
9Random ForestsF1-score0.64—Unverified
10Davinci (zero-shot)F1-score0.63—Unverified
#ModelMetricClaimedVerifiedStatus
1BERT-MRPAUROC0.86—Unverified
2BERT-RPAUROC0.85—Unverified
3BERT-HateXplain [Attn]AUROC0.85—Unverified
4BERT-HateXplain [LIME]AUROC0.85—Unverified
5BERT [Attn]AUROC0.84—Unverified
6BiRNN-HateXplain [Attn]AUROC0.81—Unverified
7BiRNN-Attn [Attn]AUROC0.8—Unverified
8CNN-GRU [LIME]AUROC0.79—Unverified
9BiRNN [LIME]AUROC0.77—Unverified
10XG-HSI-BERTAccuracy0.75—Unverified
#ModelMetricClaimedVerifiedStatus
1MLARAMHamming Loss0.29—Unverified
2MLkNNHamming Loss0.16—Unverified
3Binary RelevanceHamming Loss0.14—Unverified
4Neural Classifier ChainsHamming Loss0.13—Unverified
5Neural Binary RelevanceHamming Loss0.11—Unverified
#ModelMetricClaimedVerifiedStatus
1Mozafari et al., 2019AAA50.94—Unverified
2SVMAAA46.51—Unverified
3Kennedy et al., 2020AAA45.5—Unverified
#ModelMetricClaimedVerifiedStatus
1HateBERTMacro F10.74—Unverified
2BERTMacro F10.72—Unverified
#ModelMetricClaimedVerifiedStatus
1mBertAccuracy0.83—Unverified
2Logistic RegressionAccuracy0.7—Unverified
#ModelMetricClaimedVerifiedStatus
1HXP + CLAP + CLIPTEST F1 (macro)0.85—Unverified
2BERT + ViT + MFCCTEST F1 (macro)0.79—Unverified
#ModelMetricClaimedVerifiedStatus
1HateBERTMacro F10.49—Unverified
2BERTMacro F10.48—Unverified
#ModelMetricClaimedVerifiedStatus
1HateBERTMacro F10.81—Unverified
2BERTMacro F10.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Multilingual BERTF1-score0.75—Unverified
2AutoMLF1-score0.74—Unverified
#ModelMetricClaimedVerifiedStatus
1AOM mBERTF10.85—Unverified
#ModelMetricClaimedVerifiedStatus
1BaselineF10.7—Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-large-STMacro F180.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Baseline BERT (task A)F10.77—Unverified