A supervised learning based tool to identify toxic code review comments
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Updated
Oct 22, 2024 - Python
A supervised learning based tool to identify toxic code review comments
AntiToxicBot is a bot that detects toxics in a chat using Data Science and Machine Learning technologies. The bot will warn admins about toxic users. Also, the admin can allow the bot to ban toxics.
This is a simple python program which uses a machine learning model to detect toxicity in tweets, developed in Flask.
An anti-toxicity Discord bot to ease moderation.
This is a simple python program which uses a machine learning model to detect toxicity in tweets, GUI in Tkinter.
This demo shows the functionality of the Voximplant instant messaging SDK, including silent supervision by a bot.
This work focuses on the development of machine learning models, in particular neural networks and SVM, where they can detect toxicity in comments. The topics we will be dealing with: a) Cost-sensitive learning, b) Class imbalance
An Explainable Toxicity detector for code review comments. Published in ESEM'2023
NLP deep learning model for multilingual toxicity detection in text 📚
Comparing Toxic Texts with Transformers
This library can detect toxicity in the text or string or content and in return provide you the toxicity percentage in text or content with toxic words found in text.
Measure and mitigate gender bias in Danish toxicity classifiers and sentiment analysis models.
Toxicity detection in a conversation or phases.
Telegram bot that detects toxic comments based on Perspective API
BadFilter.js to the rescue! We’ve crafted a supercharged, customizable solution that helps developers filter out inappropriate words like a pro. Let's make the internet a friendlier place one word at a time!
Detecting Toxic comments using machine learning
This is a application to analyse toxicity in social media using BERT and context analysis and aims to reduce toxicity
In-game Toxic Language Detection: Shared Task and Attention Residuals
This repository features an LLM-based moderation system designed for game audio and text chats. By implementing toxicity moderation, it enhances the online interaction experience for gamers, improving player retention by minimizing adverse negative experiences in games such as Valorant and Overwatch. Ultimately reducing manual moderation costs.
It is a trained Deep Learning model to predict different level of toxic comments. Toxicity like threats, obscenity, insults, and identity-based hate.
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