HateBR is the first large-scale expert annotated dataset of Brazilian Instagram comments for hate speech and offensive language detection on the web and social media.
This is a python project that is used to identify hate speech in tweets. The dataset used to train the model is available on Kaggle and consists of labelled tweets where 1 indicates hate speech tweets and 0 indicates non-hate speech tweets.
[USENIX'25] HateBench: Benchmarking Hate Speech Detectors on LLM-Generated Content and Hate Campaigns
Towards a Programmable Humanizing AI through Scalable Stance-Directed Architecture
Official repository of HODI, the shared task on Homotransphobia Detection in Italian at Evalita 2023
This repository contains the code and data of the paper titled "XLNet-CNN: Combining Global Context Understanding of XLNet with Local Context Capture through Convolution for Improved Multi-Label Text Classification", which has been accepted at NSysS 2024.
UINSUSKA participation in HASOC 2023 Task 1
In this project, I focused on benchmarking various machine learning models, deep learning architectures, and fine-tuned BERT-based models to evaluate their performance across multiple metrics
CyberGuard: Machine Learning Vigilance Against Online Harassment
It detects caste based hate speech and reinforces social equality and justice
AIceberg - AI learning assistence
A Python-based data tool for Integrating Hate Speech datasets with varying schemas.
Detect hate speech in tweets using NLP and Machine Learning. This project automates classification into hate speech, offensive language, and neutral content. 🐙💻
Hate content moderation bot on Discord
Hate Speech Detection Comparative Study: GPT-3.5 vs. Fine-tuned BERT Model
The rapid growth of social media has led to an increase in user-generated content, making platforms like Twitter a major medium for public communication. However, along with positive engagement, there has also been a surge in hate speech, offensive language, and abusive content. This project aims to address this challenge by developing a ML program
A multilingual lexicon of words to hurt.
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