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
Emotion Based Hate Speech Detection using Multimodal Learning—0
Ensemble of pre-trained language models and data augmentation for hate speech detection from Arabic tweets—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
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
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
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
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
Fair Hate Speech Detection through Evaluation of Social Group Counterfactuals—0
Fairly Accurate: Learning Optimal Accuracy vs. Fairness Tradeoffs for Hate Speech Detection—0
Few-shot Hate Speech Detection Based on the MindSpore Framework—0
Fight Fire with Fire: Fine-tuning Hate Detectors using Large Samples of Generated Hate Speech—0
Fine-Grained Chinese Hate Speech Understanding: Span-Level Resources, Coded Term Lexicon, and Enhanced Detection Frameworks—0
Finnish Hate-Speech Detection on Social Media Using CNN and FinBERT—0
Free speech or Free Hate Speech? Analyzing the Proliferation of Hate Speech in Parler—0
From Universal Language Model to Downstream Task: Improving RoBERTa-Based Vietnamese Hate Speech Detection—0
Fully Connected Neural Network with Advance Preprocessor to Identify Aggression over Facebook and Twitter—0
GASCOM: Graph-based Attentive Semantic Context Modeling for Online Conversation Understanding—0
Gauravarora@HASOC-Dravidian-CodeMix-FIRE2020: Pre-training ULMFiT on Synthetically Generated Code-Mixed Data for Hate Speech Detection—0
Generative AI for Hate Speech Detection: Evaluation and Findings—0
GOF at Arabic Hate Speech 2022: Breaking The Loss Function Convention For Data-Imbalanced Arabic Offensive Text Detection—0
GPT-4V(ision) as A Social Media Analysis Engine—0
GUCT at Arabic Hate Speech 2022: Towards a Better Isotropy for Hatespeech Detection—0
Harnessing Artificial Intelligence to Combat Online Hate: Exploring the Challenges and Opportunities of Large Language Models in Hate Speech Detection—0
Harnessing Pre-Trained Sentence Transformers for Offensive Language Detection in Indian Languages—0
HashCount at SemEval-2018 Task 3: Concatenative Featurization of Tweet and Hashtags for Irony Detection—0
HateDebias: On the Diversity and Variability of Hate Speech Debiasing—0
Hateful Person or Hateful Model? Investigating the Role of Personas in Hate Speech Detection by Large Language Models—0
HateGAN: Adversarial Generative-Based Data Augmentation for Hate Speech Detection—0
HATEMINER at SemEval-2019 Task 5: Hate speech detection against Immigrants and Women in Twitter using a Multinomial Naive Bayes Classifier—0
Hate Speech and Offensive Content Detection in Indo-Aryan Languages: A Battle of LSTM and Transformers—0
Hate Speech and Offensive Language Detection using an Emotion-aware Shared Encoder—0
Hate Speech Detection and Classification in Amharic Text with Deep Learning—0
Hate Speech Detection and Racial Bias Mitigation in Social Media based on BERT model—0
Hate speech detection in algerian dialect using deep learning—0
Hate Speech Detection in Clubhouse—0
Hate Speech Detection in Limited Data Contexts using Synthetic Data Generation—0
Hate Speech Detection in Roman Urdu—0
Hate Speech Detection in Saudi Twittersphere: A Deep Learning Approach—0
Hate Speech detection in the Bengali language: A dataset and its baseline evaluation—0
Hate speech detection using static BERT embeddings—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