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 101–150 of 507 papers

TitleStatusHype
ARGUABLY at ComMA@ICON: Detection of Multilingual Aggressive, Gender Biased, and Communally Charged Tweets Using Ensemble and Fine-Tuned IndicBERT—0
Contextual Hate Speech Detection in Code Mixed Text using Transformer Based Approaches—0
Contextualizing Internet Memes Across Social Media Platforms—0
Contextual-Lexicon Approach for Abusive Language Detection—0
Cordyceps@LT-EDI: Patching Language-Specific Homophobia/Transphobia Classifiers with a Multilingual Understanding—0
Counterfactually Augmented Data and Unintended Bias: The Case of Sexism and Hate Speech Detection—0
CRAB: Class Representation Attentive BERT for Hate Speech Identification in Social Media—0
Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification—0
Explainable Identification of Hate Speech towards Islam using Graph Neural Networks—0
Cross-lingual Capsule Network for Hate Speech Detection in Social Media—0
Cross-lingual hate speech detection based on multilingual domain-specific word embeddings—0
Cross-lingual Hate Speech Detection using Transformer Models—0
Cross-Lingual Transfer Learning for Hate Speech Detection—0
Cross-lingual Zero- and Few-shot Hate Speech Detection Utilising Frozen Transformer Language Models and AXEL—0
Anti-Asian Hate Speech Detection via Data Augmented Semantic Relation Inference—0
Cross-Platform Hate Speech Detection with Weakly Supervised Causal Disentanglement—0
Crowd-Calibrator: Can Annotator Disagreement Inform Calibration in Subjective Tasks?—0
A systematic review of Hate Speech automatic detection using Natural Language Processing—0
Explaining Hate Speech Classification with Model Agnostic Methods—0
Darkness can not drive out darkness: Investigating Bias in Hate SpeechDetection Models—0
Data-Efficient Hate Speech Detection via Cross-Lingual Nearest Neighbor Retrieval with Limited Labeled Data—0
A Target-Aware Analysis of Data Augmentation for Hate Speech Detection—0
Data Expansion using Back Translation and Paraphrasing for Hate Speech Detection—0
AtteSTNet -- An attention and subword tokenization based approach for code-switched text hate speech detection—0
DeepHate: Hate Speech Detection via Multi-Faceted Text Representations—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
Bridging Modalities: Enhancing Cross-Modality Hate Speech Detection with Few-Shot In-Context Learning—0
4chan & 8chan embeddings—0
Break it, Imitate it, Fix it: Robustness by Generating Human-Like Attacks—0
A Comprehensive Study on NLP Data Augmentation for Hate Speech Detection: Legacy Methods, BERT, and LLMs—0
Evaluating Simple Debiasing Techniques in RoBERTa-based Hate Speech Detection Models—0
Explainable and High-Performance Hate and Offensive Speech Detection—0
Exploiting Explainability to Design Adversarial Attacks and Evaluate Attack Resilience in Hate-Speech Detection Models—0
Exploring new Approaches for Information Retrieval through Natural Language Processing—0
BOISHOMMO: Holistic Approach for Bangla Hate Speech—0
Beyond Toxic: Toxicity Detection Datasets are Not Enough for Brand Safety—0
HateBR: A Large Expert Annotated Corpus of Brazilian Instagram Comments for Offensive Language and Hate Speech Detection—0
Beyond Explanation: A Case for Exploratory Text Visualizations of Non-Aggregated, Annotated Datasets—0
AnnoBERT: Effectively Representing Multiple Annotators' Label Choices to Improve Hate Speech Detection—0
A Graph-Based Context-Aware Model to Understand Online Conversations—0
BERT-based Ensemble Approaches for Hate Speech Detection—0
Do Characters Abuse More Than Words?—0
An Investigation of Large Language Models for Real-World Hate Speech Detection—0
An Investigation Into Explainable Audio Hate Speech Detection—0
Digital Guardians: Can GPT-4, Perspective API, and Moderation API reliably detect hate speech in reader comments of German online newspapers?—0
DetoxBench: Benchmarking Large Language Models for Multitask Fraud & Abuse Detection—0
Determining Code Words in Euphemistic Hate Speech Using Word Embedding Networks—0
Domain Classification-based Source-specific Term Penalization for Domain Adaptation in Hate-speech Detection—0
Dominant Set-based Active Learning for Text Classification and its Application to Online Social Media—0
Bayesian Methods for Semi-supervised Text Annotation—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 [LIME]AUROC0.85—Unverified
4BERT-HateXplain [Attn]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