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 351–400 of 507 papers

TitleStatusHype
Multimodal and Explainable Internet Meme Classification—0
When the Majority is Wrong: Modeling Annotator Disagreement for Subjective Tasks—0
Multi-modal Hate Speech Detection using Machine Learning—0
Multitask Learning for Arabic Offensive Language and Hate-Speech Detection—0
A Dataset of Hindi-English Code-Mixed Social Media Text for Hate Speech Detection—0
My Boli: Code-mixed Marathi-English Corpora, Pretrained Language Models and Evaluation Benchmarks—0
A Comprehensive Study on NLP Data Augmentation for Hate Speech Detection: Legacy Methods, BERT, and LLMs—0
Navigating Dialectal Bias and Ethical Complexities in Levantine Arabic Hate Speech Detection—0
ToxSyn-PT: A Large-Scale Synthetic Dataset for Hate Speech Detection in Portuguese—0
Transferring Knowledge via Neighborhood-Aware Optimal Transport for Low-Resource Hate Speech Detection—0
Aggression Detection in Social Media: Using Deep Neural Networks, Data Augmentation, and Pseudo Labeling—0
Whose Emotions and Moral Sentiments Do Language Models Reflect?—0
NoisyHate: Mining Online Human-Written Perturbations for Realistic Robustness Benchmarking of Content Moderation Models—0
Trustworthy Hate Speech Detection Through Visual Augmentation—0
TuEval at SemEval-2019 Task 5: LSTM Approach to Hate Speech Detection in English and Spanish—0
Offensive Language and Hate Speech Detection for Danish—0
Offensive Language and Hate Speech Detection with Deep Learning and Transfer Learning—0
On a Benefit of Mask Language Modeling: Robustness to Simplicity Bias—0
One to rule them all: Towards Joint Indic Language Hate Speech Detection—0
On Fairness of Task Arithmetic: The Role of Task Vectors—0
On Importance of Code-Mixed Embeddings for Hate Speech Identification—0
On Limitations of LLM as Annotator for Low Resource Languages—0
Online Hate: Behavioural Dynamics and Relationship with Misinformation—0
On the Challenges of Building Datasets for Hate Speech Detection—0
A Legal Approach to Hate Speech -- Operationalizing the EU's Legal Framework against the Expression of Hatred as an NLP Task—0
A Federated Approach to Few-Shot Hate Speech Detection for Marginalized Communities—0
OSACT4 Shared Task on Offensive Language Detection: Intensive Preprocessing-Based Approach—0
OSACT4 Shared Tasks: Ensembled Stacked Classification for Offensive and Hate Speech in Arabic Tweets—0
BanglaEmbed: Efficient Sentence Embedding Models for a Low-Resource Language Using Cross-Lingual Distillation Techniques—0
BanTH: A Multi-label Hate Speech Detection Dataset for Transliterated Bangla—0
Overview of OSACT5 Shared Task on Arabic Offensive Language and Hate Speech Detection—0
Bayesian Methods for Semi-supervised Text Annotation—0
Author Profiling for Hate Speech Detection—0
Overview of the HASOC track at FIRE 2020: Hate Speech and Offensive Content Identification in Indo-European Languages—0
BERT-based Ensemble Approaches for Hate Speech Detection—0
BERT or FastText? A Comparative Analysis of Contextual as well as Non-Contextual Embeddings—0
Beyond Explanation: A Case for Exploratory Text Visualizations of Non-Aggregated, Annotated Datasets—0
Beyond Toxic: Toxicity Detection Datasets are Not Enough for Brand Safety—0
BOISHOMMO: Holistic Approach for Bangla Hate Speech—0
Measuring Catastrophic Forgetting in Cross-Lingual Transfer Paradigms: Exploring Tuning Strategies—0
Break it, Imitate it, Fix it: Robustness by Generating Human-Like Attacks—0
Bridging Modalities: Enhancing Cross-Modality Hate Speech Detection with Few-Shot In-Context Learning—0
Bridging the gap in online hate speech detection: a comparative analysis of BERT and traditional models for homophobic content identification on X/Twitter—0
A Unified Multi-Task Learning Architecture for Hate Detection Leveraging User-Based Information—0
ABARUAH at SemEval-2019 Task 5 : Bi-directional LSTM for Hate Speech Detection—0
Can Prompting LLMs Unlock Hate Speech Detection across Languages? A Zero-shot and Few-shot Study—0
Afaan Oromo Hate Speech Detection and Classification on Social Media—0
Ceasing hate withMoH: Hate Speech Detection in Hindi-English Code-Switched Language—0
Chain-of-Translation Prompting (CoTR): A Novel Prompting Technique for Low Resource Languages—0
A Comparative Study of Different State-of-the-Art Hate Speech Detection Methods in Hindi-English Code-Mixed Data—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