YouTube Sentiment Analyzer

Overview

This is a Python project that analyzes the sentiment of comments on YouTube videos. It uses the VADER sentiment analysis tool and TF-IDF to provide further information on what the comments think about the video. It also has a frontend powered by Flask.

✨ Features

• Fetch comments from YouTube videos using the YouTube Data API.

• Analyze the sentiment of comments using VADER.

• Generate a wordcloud from the most important words.

📝 Prerequisites

• Python with PIP installed
• YouTube Data API key

Note

Although this is a NodeJS project too, having node_modules installed is required only if editing TailwindCSS.

💽 Installation

1. Clone the repo:

   $ git clone https://github.com/keanegrech/youtube-sentiment-analyzer.git
   $ cd youtube-sentiment-analyzer

2. Set up your API key:

   • Rename example.env to .env
   • Add your API key to YSA_DATA_API_KEY="your key here"

3. Run setup.py to install all required dependencies.

🎚️ Usage

1. Run the Flask app:

   Start the Flask web server to use the frontend

   $ python main.py

2. Access the web interface

   Open your web browser and go to http://127.0.0.1:5000

   The default port is 5000, it can be changed from the .env file.

3. Fetch comments:

   Enter either a YouTube URL or video ID followed by the sample size of comments to begin processing.

4. Results:

   • You can see the videos title, like and comment count
   • See overall sentiment
   • See most positive and negative comment and their respective sentiment scores
   • Download comments as a txt file
   • Download word cloud of most important words