Build Healthier Communities With Real-Time AI!
This Solution Accelerator helps you detect toxic in-game chat in real time so you can protect players, reduce churn and keep your gaming communities engaged and healthy. It shows you how to use a lakehouse plus NLP to ingest and analyze gamer data, flag toxic messages and support your moderation teams with scalable, automated workflows.
Key highlights
- Pre-built Databricks notebook with code, sample data and step-by-step guidance to get started quickly
- Real-time detection of toxic comments in in-game chat using multi-label NLP models
- Lakehouse-based architecture to unify chat, gameplay and other gamer data (streams, files, voice and more)
- Built-in ML pipeline to train and track toxicity models and a streaming pipeline for real-time inference
- Designed to plug into existing community moderation processes and tools to improve player experience and retention
Ready to tackle toxicity in your games? Import the Toxicity Detection in Gaming Solution Accelerator into your Databricks workspace and start building real-time toxicity detection and moderation workflows today.
You can also refer to this article for a complete overview of Toxicity Detection in Gaming.
