Hazrat-Ali9/Multi-Label-Toxic-Comment-Detection-With-Deep-Learning
🪣 Multi 🧰 Label 📒 Toxic 📓 Comment 📘 Detection 📙 Deep 📔 Learning 📚 is an NLP ☎ designed to 📹 automatically ⚽ detect 🏈 classify ⚾ toxic 🥎 comments 🏀 into ⛸ multiple 📟 categories ✈ such as toxic 🚀 severe 🚁obscene 🛬 threat ⛴ insult 🚟 identity 🛸 deep 🚞 models it 🚃 helps build 🛼 inclusive 🚂 communities 🏰 by filtering 🏘 harmful 🥋
This project helps online community managers, social media platforms, and content moderators automatically identify and categorize harmful comments. It takes in user-generated text, like comments on a blog or social media, and outputs classifications such as 'toxic', 'threat', or 'insult', even if a single comment falls into multiple categories. This allows for real-time filtering and moderation to foster safer online environments.
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Use this if you manage an online platform and need to automatically detect and classify various forms of toxic language to enforce community guidelines.
Not ideal if you need to moderate non-English content or require sentiment analysis beyond toxicity detection.
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Sep 13, 2025
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