CommentSense is an intelligent tool that leverages OpenAI’s Large Language Models (LLMs) to analyze YouTube comments and generate high-level feedback for content creators. Just paste a YouTube link, and CommentSense will summarize what your audience thinks — the good, the bad, and what they want next.
📌 Designed for creators, brand strategists, and YouTube growth hackers.
- 🔗 Input any YouTube video link
- 🤖 Automatically fetches comments using the YouTube Data API
- 🧠 Uses OpenAI GPT to analyze:
- ✅ Overall audience sentiment
- ✅ Strengths of the video
- ✅ Weaknesses or pain points
- ✅ Suggestions or requests from viewers
- 📊 Outputs clean, structured insights
- 🖥️ Visualized with Gradio UI
- Content Creators – Understand viewer feedback and plan better content
- Marketing Teams – Gauge brand reception and viewer language
- Researchers – Track sentiment trends and audience behavior
- Developers – Build custom tools around YouTube engagement
- User enters a YouTube video URL
- Tool extracts the video ID
- Fetches up to 100 top-level comments using the YouTube Data API v3
- Sends comment list to OpenAI GPT-4 with the following prompt:
system_message = "You are an assistant that analyses YouTube comments"
user_prompt = f"""Analyse the following comments and tell the channel owner:
1. Overall audience sentiment
2. Strengths of the video
3. Weaknesses
4. Future content demands or suggestions from viewers.
Comments: {comments_list}- Returns a structured analysis for the creator to act on.
git clone https://github.com/johnIT56/CommentSense.git
cd CommentSense
pip install -r requirements.txt
python app.py
💡 You’ll need a YouTube Data API key and an OpenAI API key set up in your environment or a config file.
🧑💻 Contributing Contributions are welcome! Please open issues or pull requests to improve functionality, UI, or model prompts.
📜 License MIT License
📫 Contact
Built with 💡 by johnIT56
📧 Email: johnsonmoshy6@gmail.com