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
Offence in Dialogues: A Corpus-Based StudyCode0
Multilingual and Multi-Aspect Hate Speech AnalysisCode0
Offensive Language and Hate Speech Detection for Danish—0
Multi-label Hate Speech and Abusive Language Detection in Indonesian TwitterCode0
L-HSAB: A Levantine Twitter Dataset for Hate Speech and Abusive Language—0
Multilingual and Multitarget Hate Speech Detection in Tweets—0
The Risk of Racial Bias in Hate Speech Detection—0
Exploiting Unsupervised Pre-training and Automated Feature Engineering for Low-resource Hate Speech Detection in Polish—0
Improved Sentiment Detection via Label Transfer from Monolingual to Synthetic Code-Switched TextCode0
Privacy-Preserving Classification of Personal Text Messages with Secure Multi-Party Computation: An Application to Hate-Speech Detection—0
UA at SemEval-2019 Task 5: Setting A Strong Linear Baseline 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
YNU NLP at SemEval-2019 Task 5: Attention and Capsule Ensemble for Identifying Hate Speech—0
The binary trio at SemEval-2019 Task 5: Multitarget Hate Speech Detection in Tweets—0
Tw-StAR at SemEval-2019 Task 5: N-gram embeddings for Hate Speech Detection in Multilingual Tweets—0
Vista.ue at SemEval-2019 Task 5: Single Multilingual Hate Speech Detection Model—0
ABARUAH at SemEval-2019 Task 5 : Bi-directional LSTM for Hate Speech Detection—0
CIC at SemEval-2019 Task 5: Simple Yet Very Efficient Approach to Hate Speech Detection, Aggressive Behavior Detection, and Target Classification in Twitter—0
INF-HatEval at SemEval-2019 Task 5: Convolutional Neural Networks for Hate Speech Detection Against Women and Immigrants on Twitter—0
MITRE at SemEval-2019 Task 5: Transfer Learning for Multilingual Hate Speech Detection—0
SSN\_NLP at SemEval-2019 Task 6: Offensive Language Identification in Social Media using Traditional and Deep Machine Learning Approaches—0
sthruggle at SemEval-2019 Task 5: An Ensemble Approach to Hate Speech Detection—0
TuEval at SemEval-2019 Task 5: LSTM Approach to Hate Speech Detection in English and Spanish—0
STUFIIT at SemEval-2019 Task 5: Multilingual Hate Speech Detection on Twitter with MUSE and ELMo Embeddings—0
Know-Center at SemEval-2019 Task 5: Multilingual Hate Speech Detection on Twitter using CNNs—0
Author Profiling for Hate Speech Detection—0
Hateminers : Detecting Hate speech against WomenCode0
Hate Speech Detection from Code-mixed Hindi-English Tweets Using Deep Learning ModelsCode0
Interpreting Neural Network Hate Speech Classifiers—0
Why Swear? Analyzing and Inferring the Intentions of Vulgar Expressions—0
The Effects of User Features on Twitter Hate Speech Detection—0
Determining Code Words in Euphemistic Hate Speech Using Word Embedding Networks—0
Predictive Embeddings for Hate Speech Detection on Twitter—0
Detecting Hate Speech and Offensive Language on Twitter using Machine Learning: An N-gram and TFIDF based Approach—0
Hate Speech Dataset from a White Supremacy ForumCode0
Hierarchical CVAE for Fine-Grained Hate Speech Classification—0
All You Need is "Love": Evading Hate-speech Detection—0
Fully Connected Neural Network with Advance Preprocessor to Identify Aggression over Facebook and Twitter—0
Aggression Detection in Social Media: Using Deep Neural Networks, Data Augmentation, and Pseudo Labeling—0
Detecting Offensive Tweets in Hindi-English Code-Switched Language—0
A Dataset of Hindi-English Code-Mixed Social Media Text for Hate Speech Detection—0
HashCount at SemEval-2018 Task 3: Concatenative Featurization of Tweet and Hashtags for Irony Detection—0
Examining a hate speech corpus for hate speech detection and popularity predictionCode0
Improving Hate Speech Detection with Deep Learning EnsemblesCode0
Leveraging Intra-User and Inter-User Representation Learning for Automated Hate Speech Detection—0
Hate Speech Detection: A Solved Problem? The Challenging Case of Long Tail on TwitterCode0
Surfacing contextual hate speech words within social mediaCode0
Recognizing Explicit and Implicit Hate Speech Using a Weakly Supervised Two-path Bootstrapping Approach—0
Detecting Online Hate Speech Using Context Aware ModelsCode0
Class-based Prediction Errors to Detect Hate Speech with Out-of-vocabulary Words—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