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 301–350 of 507 papers

TitleStatusHype
Analyzing the Real Vulnerability of Hate Speech Detection Systems against Targeted Intentional Noise—0
Know-Center at SemEval-2019 Task 5: Multilingual Hate Speech Detection on Twitter using CNNs—0
L3Cube-MahaHate: A Tweet-based Marathi Hate Speech Detection Dataset and BERT models—0
L3Cube-MahaNLP: Marathi Natural Language Processing Datasets, Models, and Library—0
ToKen: Task Decomposition and Knowledge Infusion for Few-Shot Hate Speech Detection—0
LAHM : Large Annotated Dataset for Multi-Domain and Multilingual Hate Speech Identification—0
LAMPO: Large Language Models as Preference Machines for Few-shot Ordinal Classification—0
Large-Scale Hate Speech Detection with Cross-Domain Transfer—0
Analysis and Detection of Multilingual Hate Speech Using Transformer Based Deep Learning—0
A multilingual dataset for offensive language and hate speech detection for hausa, yoruba and igbo languages—0
Towards A Multi-agent System for Online Hate Speech Detection—0
Learning Domain Terms - Empirical Methods to Enhance Enterprise Text Analytics Performance—0
American Hate Crime Trends Prediction with Event Extraction—0
Leveraging Affective Bidirectional Transformers for Offensive Language Detection—0
Leveraging Annotator Disagreement for Text Classification—0
Leveraging cross-platform data to improve automated hate speech detection—0
Leveraging Intra-User and Inter-User Representation Learning for Automated Hate Speech Detection—0
Wisdom of Instruction-Tuned Language Model Crowds. Exploring Model Label Variation—0
Leveraging Language Identification to Enhance Code-Mixed Text Classification—0
Towards Argument Mining for Social Good: A Survey—0
Watching the Watchers: A Comparative Fairness Audit of Cloud-based Content Moderation Services—0
Leveraging Transformers for Hate Speech Detection in Conversational Code-Mixed Tweets—0
Leveraging Weakly Annotated Data for Hate Speech Detection in Code-Mixed Hinglish: A Feasibility-Driven Transfer Learning Approach with Large Language Models—0
Leveraging World Knowledge in Implicit Hate Speech Detection—0
Towards Code-switched Classification Exploiting Constituent Language Resources—0
L-HSAB: A Levantine Twitter Dataset for Hate Speech and Abusive Language—0
LLMs and Finetuning: Benchmarking cross-domain performance for hate speech detection—0
mahaNLP: A Marathi Natural Language Processing Library—0
Towards countering hate speech against journalists on social media—0
Meta AI at Arabic Hate Speech 2022: MultiTask Learning with Self-Correction for Hate Speech Classification—0
Zero-shot Cross-lingual Content Filtering: Offensive Language and Hate Speech Detection—0
MHS-STMA: Multimodal Hate Speech Detection via Scalable Transformer-Based Multilevel Attention Framework—0
Towards Fairness Assessment of Dutch Hate Speech Detection—0
Mitigating Label Bias via Decoupled Confident Learning—0
MITRE at SemEval-2019 Task 5: Transfer Learning for Multilingual Hate Speech Detection—0
Towards generalisable hate speech detection: a review on obstacles and solutions—0
Model-Agnostic Meta-Learning for Multilingual Hate Speech Detection—0
Mono vs Multilingual BERT for Hate Speech Detection and Text Classification: A Case Study in Marathi—0
Mpox Narrative on Instagram: A Labeled Multilingual Dataset of Instagram Posts on Mpox for Sentiment, Hate Speech, and Anxiety Analysis—0
ALT Submission for OSACT Shared Task on Offensive Language Detection—0
What is the social benefit of hate speech detection research? A Systematic Review—0
All You Need is "Love": Evading Hate-speech Detection—0
Towards hate speech detection in low-resource languages: Comparing ASR to acoustic word embeddings on Wolof and Swahili—0
Multilingual acoustic word embeddings for zero-resource languages—0
Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models—0
Multilingual and Multitarget Hate Speech Detection in Tweets—0
When More is not Necessary Better: Multilingual Auxiliary Tasks for Zero-Shot Cross-Lingual Transfer of Hate Speech Detection Models—0
A Legal Approach to Hate Speech – Operationalizing the EU’s Legal Framework against the Expression of Hatred as an NLP Task—0
Multilingual Hate Speech Detection in Social Media Using Translation-Based Approaches with Large Language Models—0
A Graph-Based Context-Aware Model to Understand Online Conversations—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