offensive-language
There are 63 repositories under offensive-language topic.
t-davidson/hate-speech-and-offensive-language
Repository for the paper "Automated Hate Speech Detection and the Problem of Offensive Language", ICWSM 2017
vzhou842/profanity-check
A fast, robust Python library to check for offensive language in strings.
axenhammer/CODAR
✅ CODAR is a framework built using PyTorch to analyze post (Text+Media) and predict cyber bullying and offensive content.
ahmedhammad97/Offensive-Language-Detection
NLP model that uses Machine Learning to detect offensive tweets, and classify it's target.
thefirebanks/Ensemble-Learning-for-Tweet-Classification-of-Hate-Speech-and-Offensive-Language
Contains code for a voting classifier that is part of an ensemble learning model for tweet classification (which includes an LSTM, a bayesian model and a proximity model) and a system for weighted voting
MilaNLProc/honest
A Python package to compute HONEST, a score to measure hurtful sentence completions in language models. Published at NAACL 2021.
richouzo/hate-speech-detection-survey
Trained Neural Networks (LSTM, HybridCNN/LSTM, PyramidCNN, Transformers, etc.) & comparison for the task of Hate Speech Detection on the OLID Dataset (Tweets).
jakubsadura/eslint-plugin-no-shit
Disallow ⚠️ use of offensive 💪 language 💯
TiagoMAntunes/KAREN
KAREN: Unifying Hatespeech Detection and Benchmarking
tailaiw/mind-your-language-action
A GitHub action that monitors PR/issue comments and warns senders who used offensive language.
YYYIKES/insult-generator
Offend your friends and family! Generate scathing insults based on an edited dataset of insults scraped from various places around the web.
Tanat05/korean-profanity-resources
한국어 욕설, 비속어, 혐오 표현(offensive language) 관련 데이터셋, 라이브러리, API를 모아놓은 리소스 저장소
DivineOmega/laravel-offensive-validation-rule
🤬🤭 Laravel validation rule that checks if a string is offensive.
tommasoc80/DALC
Dutch abusive language data
AfriHate/AfriHate
This is a repository for AfriHate Project
hate-alert/HateALERT-HASOC
Code for replicating the results of "HateMonitors" at HASOC 2019
DivineOmega/is_offensive
🤬🤭 Is Offensive Helper Function - Check if a string contains offensive words or variations of them
motazsaad/arabic-hatespeech-data
Arabic hate speech data
circa10a/react-foaas-card
The most offensive of react components
ciwang/deep_hatespeech
Classifying hate speech with deep learning (honors thesis 2017-18)
alpcansoydas/turkish-hate-speech-analysis
Turkish Hate Speech Detection
laravel-validation-rules/offensive
This rule will validate that a field isn't offensive.
ddindidu/K-OMG
Example dataset and prompt design of Korean Offensive language Machine Generation (K-OMG), published at IJCNLP-AACL 2023.
DivineOmega/php-word-info
PHP library to look up information about words
MelinaPl/speech-act-analysis
A speech act analysis of offensive language in German Tweets - an annotated datatset.
suhjohn/offensive-text-filter
CNN-based Twitter offensive text classification model
Luxshan2000/dravida-kavacham
DravidaKavacham is an open-source tool for detecting abusive content in Dravidian (Tamil and Malayalam), focused on harmful language targeting women. Developed as part of the DravidianLangTech@NAACL 2025 shared task, it uses NLP and machine learning for accurate text classification and content analysis.
merishnaSuwal/nep-off-langdetect
Offensive language detection and sentiment analysis on Nepali text
purveshpatel511/offensive-hateful-text-multiclassification
This is NLP project of text multi-classification. My pre-trained model classify speech into three different categories offensive, hateful and neither.
rnegron/django-profanity-check
A Django template filter that wraps around profanity-check
Strifee/offensive_Arabic
Arabic offensive speach detector with Arabic BERT and Pytorch
talhaanwarch/OffenseEval2020
OffenseEval2020 Competetion
aehabV/Hate-Speech-Detection-on-Arabic-Tweets
We utilized a pre-trained model to classify Arabic text. After conducting extensive research, we found that MarBERT was the best model for classifying Arabic offensive tweets. It focuses on dialectal Arabic (DA) and Modern Standard Arabic (MSA). The competition involves two shared sub-tasks: detecting whether a tweet is offensive or not; and detecting whether a tweet contains hate speech or not. It detected offensive sentences with 84.9% accuracy and F1-Score of 83.5%, and hate speech with 93.4% accuracy and F1-Score of 80.4%.
arunavsk/OffenseEval2019
Offensive Language Identification and Categorization
daconjam/Harmful-LGBTQIA
Detecting Harmful Online Conversational Content towards LGBTQIA+ Individuals