toxicg

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  ROC scores

Inspiration

ToxicityClassifier is a specialized tool designed to identify and filter toxic language within gaming environments or online chat platforms. It leverages machine learning to analyze text in real-time, helping moderators or automated systems maintain a healthier community by flagging offensive, abusive, or harmful content.

Key Features Real-time Detection: Capable of processing chat streams quickly to identify toxicity as it happens.

Multi-Category Classification: Rather than just a binary "toxic or not," it often categorizes types of toxicity, such as:

Insults

Threats

Obscenity

Identity-based hate

Lightweight Integration: Designed to be integrated into Discord bots, game servers, or web applications via an API or local module.

Customizable Thresholds: Allows administrators to define what level of "toxicity" triggers an action (e.g., a warning vs. an automatic kick).

Technical Context The project typically utilizes a Natural Language Processing (NLP) backend. Depending on the version you are looking at, it may use:

TensorFlow or PyTorch: For the heavy-lifting machine learning models.

Dataset: Trained on datasets like the Civil Comments or Jigsaw Toxic Comment Classification data to ensure high accuracy across different slang and contexts.

Use Case Example Imagine a competitive game lobby where tensions run high. ToxicG acts as a silent referee. If a player sends a message that exceeds the "Severe Toxicity" threshold, the system can automatically redact the message or log it for a human moderator to review later, preventing the situation from escalating.

What it does

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for toxicg

Built With

• pytorch
• tensorflow