YouTube Trend Analyzer

An AI-powered tool that analyzes trending YouTube content across multiple countries including US, India, UK, and more. Discover popular video formats, optimal durations, and emerging topics through interactive visualizations. Get strategic insights to inform your content strategy.

Features

• Trend Analysis: Identify popular video formats, optimal durations, and trending topics
• Multi-Region Support: Compare trends across different countries (US, India, UK, Canada, etc.)
• Interactive Visualizations: Explore data through dynamic, interactive charts
• AI-Powered Insights: Generate strategic content recommendations using advanced AI

Installation

1. Clone the repository:

   git clone https://github.com/YOUR_USERNAME/YouTube-Trend-Analyzer.git
   cd YouTube-Trend-Analyzer

2. Install required packages:

   pip install -r requirements.txt

3. Create a config.py file with your API keys:

   YouTube Data API key (required)
   YOUTUBE_API_KEY = "YOUR_YOUTUBE_API_KEY"
   
   Pollinations AI API URL (optional, for AI insights)
   POLLINATIONS_API_URL = "https://text.pollinations.ai/openai"
   
   Regions to track
   REGIONS = ['US', 'IN', 'GB', 'CA', 'AU', 'JP', 'KR', 'FR', 'DE', 'BR']
   
   Categories to track
   CATEGORIES = {
       '0': 'All',
       '10': 'Music',
       '20': 'Gaming',
       '23': 'Comedy',
       '24': 'Entertainment',
       '28': 'Science & Technology'
   }
   
   # Maximum results per API call
   MAX_RESULTS = 50

4. Create required directories:

   mkdir -p data/insights

Usage

1. Run the dashboard:

   streamlit run dashboard.py

2. To collect data, analyze trends, and generate insights via command line:

   python main.py --collect --analyze --insights

3. For help with command line options:

   python main.py --help

How It Works

1. Data Collection: The system connects to the YouTube API and collects metadata from trending videos across different categories and regions.

2. Pattern Analysis: Sophisticated algorithms analyze the collected data to identify patterns in video formats, durations, titles, and tags.

3. Visualization: The analyzed data is transformed into interactive visualizations that make it easy to understand complex trend patterns.

4. AI Insights: Advanced AI models analyze the trends to generate strategic insights and content recommendations.

Project Structure

YouTube-Trend-Analyzer/
├── config.py               # Configuration and API keys
├── dashboard.py            # Streamlit dashboard interface
├── data_collector.py       # YouTube API interaction
├── trend_analyzer.py       # Trend analysis logic
├── llm_insights.py         # AI-powered insights
├── main.py                 # Command-line interface
├── requirements.txt        # Project dependencies
└── data/                   # Data storage directory
    └── insights/           # Generated AI insights

Technical Details

This application is built using:

• YouTube Data API for trending video data collection
• Python for data processing and analysis
• Streamlit for the interactive dashboard
• Plotly for dynamic data visualizations
• Pollinations AI for generating content insights

The YouTube Data API has a daily quota limit of 10,000 units. Each data collection uses approximately 100 units, allowing for multiple collections per day.

License

This project is licensed under the MIT License.