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 451–500 of 507 papers

TitleStatusHype
Resources for Multilingual Hate Speech Detection—0
Detecting Optimism in Tweets using Knowledge Distillation and Linguistic Analysis of Optimism—0
Detection of Hate Speech using BERT and Hate Speech Word Embedding with Deep Model—0
Determining Code Words in Euphemistic Hate Speech Using Word Embedding Networks—0
DetoxBench: Benchmarking Large Language Models for Multitask Fraud & Abuse Detection—0
Digital Guardians: Can GPT-4, Perspective API, and Moderation API reliably detect hate speech in reader comments of German online newspapers?—0
A Study on Bias Detection and Classification in Natural Language Processing—0
Do Characters Abuse More Than Words?—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
Don't Go To Extremes: Revealing the Excessive Sensitivity and Calibration Limitations of LLMs in Implicit Hate Speech Detection—0
Rethinking Hate Speech Detection on Social Media: Can LLMs Replace Traditional Models?—0
UA at SemEval-2019 Task 5: Setting A Strong Linear Baseline for Hate Speech Detection—0
Effect of Word Embedding Models on Hate and Offensive Speech Detection—0
On Transferability of Bias Mitigation Effects in Language Model Fine-Tuning—0
Robust Hate Speech Detection in Social Media: A Cross-Dataset Empirical Evaluation—0
Role of Artificial Intelligence in Detection of Hateful Speech for Hinglish Data on Social Media—0
Emotion Based Hate Speech Detection using Multimodal Learning—0
UMUTextStats: A linguistic feature extraction tool for Spanish—0
Assessing the impact of contextual information in hate speech detection—0
ARGUABLY at ComMA@ICON: Detection of Multilingual Aggressive, Gender Biased, and Communally Charged Tweets Using Ensemble and Fine-Tuned IndicBERT—0
Ensemble of pre-trained language models and data augmentation for hate speech detection from Arabic tweets—0
A Review of Challenges in Machine Learning based Automated Hate Speech Detection—0
ARC-NLP at Multimodal Hate Speech Event Detection 2023: Multimodal Methods Boosted by Ensemble Learning, Syntactical and Entity Features—0
Evaluating ChatGPT's Performance for Multilingual and Emoji-based Hate Speech Detection—0
Evaluating Semantic Feature Representations to Efficiently Detect Hate Intent on Social Media—0
Evaluating Simple Debiasing Techniques in RoBERTa-based Hate Speech Detection Models—0
Safe Guard: an LLM-agent for Real-time Voice-based Hate Speech Detection in Social Virtual Reality—0
YNU NLP at SemEval-2019 Task 5: Attention and Capsule Ensemble for Identifying Hate Speech—0
Sarang at DEFACTIFY 4.0: Detecting AI-Generated Text Using Noised Data and an Ensemble of DeBERTa Models—0
Explainable and High-Performance Hate and Offensive Speech Detection—0
Explainable Identification of Hate Speech towards Islam using Graph Neural Networks—0
Explaining Hate Speech Classification with Model Agnostic Methods—0
Exploiting Explainability to Design Adversarial Attacks and Evaluate Attack Resilience in Hate-Speech Detection Models—0
Securing Social Spaces: Harnessing Deep Learning to Eradicate Cyberbullying—0
Exploiting Unsupervised Pre-training and Automated Feature Engineering for Low-resource Hate Speech Detection in Polish—0
Exploring Data Augmentation Strategies for Hate Speech Detection in Roman Urdu—0
Understanding and Interpreting the Impact of User Context in Hate Speech Detection—0
Selective Demonstration Retrieval for Improved Implicit Hate Speech Detection—0
Exploring Large Language Models for Hate Speech Detection in Rioplatense Spanish—0
Exploring new Approaches for Information Retrieval through Natural Language Processing—0
Exploring Stylometric and Emotion-Based Features for Multilingual Cross-Domain Hate Speech Detection—0
Exploring the Adversarial Capabilities of Large Language Models—0
SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)—0
Unraveling Social Perceptions & Behaviors towards Migrants on Twitter—0
Exposing the limits of Zero-shot Cross-lingual Hate Speech Detection—0
俄语网络仇恨言论语料库研究与构建(An Russian Internet Corpus for Hate Speech Detection)—0
Ara-Women-Hate: An Annotated Corpus Dedicated to Hate Speech Detection against Women in the Arabic Community—0
Fair Hate Speech Detection through Evaluation of Social Group Counterfactuals—0
Fairly Accurate: Learning Optimal Accuracy vs. Fairness Tradeoffs for Hate Speech Detection—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