https://github.com/muhammadadilnaeem/youtube-video-sentiment-and-summarization
The YouTube Video Sentiment and Summarization project is a comprehensive tool designed to analyze YouTube videos by transcribing their content, summarizing it, and performing sentiment analysis on the comments. This project leverages advanced machine learning models and APIs to provide insightful data.
https://github.com/muhammadadilnaeem/youtube-video-sentiment-and-summarization
gemini-api github google markdown project-repository python sentiment-analysis streamlit summarization transcribe youtube youtube-api-v3
Last synced: 7 months ago
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The YouTube Video Sentiment and Summarization project is a comprehensive tool designed to analyze YouTube videos by transcribing their content, summarizing it, and performing sentiment analysis on the comments. This project leverages advanced machine learning models and APIs to provide insightful data.
- Host: GitHub
- URL: https://github.com/muhammadadilnaeem/youtube-video-sentiment-and-summarization
- Owner: muhammadadilnaeem
- License: mit
- Created: 2024-07-27T06:54:05.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-10-09T11:30:44.000Z (about 1 year ago)
- Last Synced: 2025-02-01T15:40:56.620Z (9 months ago)
- Topics: gemini-api, github, google, markdown, project-repository, python, sentiment-analysis, streamlit, summarization, transcribe, youtube, youtube-api-v3
- Language: Python
- Homepage:
- Size: 13.7 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
---
# **🎥 YouTube Video Sentiment and Summarization ✨**
https://github.com/user-attachments/assets/93862faf-f461-459e-8832-09afdbb5e3ef
## **Table of Contents 📑**
- [Overview](#overview)
- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)
- [Real-Life Applications](#real-life-applications)
- [License](#license)
## **Overview 📝**
The **YouTube Video Sentiment and Summarization** project is a comprehensive tool designed to analyze YouTube videos by transcribing their content, summarizing it, and performing sentiment analysis on the comments. This project leverages advanced machine learning models and APIs to provide insightful data, making it easier for users to understand the overall reception and content of YouTube videos.
## **Features ✨**
- **Transcribe YouTube Videos:** Automatically convert spoken content in videos to text. 🗣️➡️📄
- **Summarize Transcripts:** Generate concise summaries of video content. ✍️
- **Sentiment Analysis:** Analyze the sentiment of comments left on YouTube videos. 😊😐😢
- **Metadata Display:** Display video metadata such as the number of views, channel information, and comment count. 📊📈
- **Interactive Dashboard:** User-friendly interface built with Streamlit for easy interaction and visualization. 📊🎛️
## **Installation 🛠️**
### **Prerequisites ✅**
- Python 3.7 or higher 🐍
- Streamlit 🌟
- OpenAI API Key 🔑
- Google API Key 🔑
### **Steps 📝**
1. Clone the repository:
```bash
git clone https://github.com/muhammadadilnaeem/YouTube-Video-Sentiment-and-Summarization.git
cd YouTube-Video-Sentiment-and-Summarization
```
2. Install the required dependencies:
```bash
pip install -r requirements.txt
```
3. Set up environment variables for API keys:
```bash
export OPENAI_API_KEY='your_openai_api_key'
export GOOGLE_API_KEY='your_google_api_key'
```
## **Usage 🚀**
1. Run the Streamlit app:
```bash
streamlit run app.py
```
2. Open your web browser and go to `http://localhost:8501`.
3. Enter a YouTube video URL and click on 'Submit URL' to start the analysis.
4. View the transcriptions, summaries, and sentiment analysis results on the dashboard.
## **Real-Life Applications 🌐**
### **Content Creators 🎬**
- **Insightful Feedback:** Understand the audience's sentiment towards your videos through comment analysis. 📈
- **Content Summary:** Quickly generate summaries of your videos for promotional content or quick reviews. 📝
### **Marketers 📊**
- **Audience Engagement:** Gauge viewer reactions and engagement to tailor marketing strategies. 🎯
- **Trend Analysis:** Identify trending topics and sentiment to align marketing campaigns. 📊
### **Researchers 🔍**
- **Content Analysis:** Analyze large volumes of video content for research purposes. 📚
- **Public Opinion:** Study public opinion on various topics based on video comments. 🗣️
### **Educators 👩🏫**
- **Content Summarization:** Provide students with concise summaries of educational videos. 📚
- **Feedback Analysis:** Analyze student feedback to improve educational content. 🎓
## **License 📄**
This project is licensed under the MIT License. See the [LICENSE](https://github.com/muhammadadilnaeem/YouTube-Video-Sentiment-and-Summarization/blob/main/LICENSE) file for more details.
---