Offend your friends and family! Generate scathing insults based on an edited dataset of insults scraped from various places around the web.
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Updated
Jun 6, 2024 - Python
Offend your friends and family! Generate scathing insults based on an edited dataset of insults scraped from various places around the web.
HausaHate is a benchmark dataset for Hausa hate speech detection task. it was extracted from West African Facebook pages and comprises 2,000 comments annotated according to a binary class (offensive and non-offensive) and hate speech targets (race, gender and none).
A Brazilian Portuguese Text Offensiveness Analysis System
A fast, robust Python library to check for offensive language in strings.
🔍 Ensuring community harmony and shielding against ads and harassment with DFA-based offensive language detection. 🌐💬
Data and code for paper: Context-Aware Offensive Language Detection in Human-Chatbot Conversations
This is a repository for AfriHate Project
API para Decteção de comentários Ofensivos
Example dataset and prompt design of Korean Offensive language Machine Generation (K-OMG), published at IJCNLP-AACL 2023.
Offensive language detection and sentiment analysis on Nepali text
Translated abusive language dataset (En2Ko). Including OffensEval/AbusEval, CADD, Davidson et al., Waseem&Hovy.
A speech act analysis of offensive language in German Tweets - an annotated datatset.
Dutch abusive language data
Using weak supervision to perform named entity recognition and offensive language detection on r/sg comments
a novel Romanian language dataset for offensive message detection with manually annotated comment from a local Romanian news website (stiri de cluj) into five classes
Repository for the paper "Automated Hate Speech Detection and the Problem of Offensive Language", ICWSM 2017
Turkish Hate Speech Detection
A Django template filter that wraps around profanity-check
This is NLP project of text multi-classification. My pre-trained model classify speech into three different categories offensive, hateful and neither.
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