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Sentiment Analysis for YouTube Videos

This repository offers a solution to analyze sentiments for a specified YouTube video.

Approach:

  1. YouTube Comment Scraping:

    • Utilizes the video's ID to scrape comments from the YouTube platform.
  2. Language Standardization:

    • Converts all extracted comments into a unified language (English) for consistent analysis.
  3. Sentiment Analysis Model:

    • Employing a pre-trained sentiment analysis model. For simplicity, this example employs the VADER sentiment analysis tool.
  4. Temporal Sentiment Trend Analysis:

    • Calculates the sentiment trend over a specified time period to reveal fluctuations in sentiment over time.

How it Works:

  1. Input: Provide the YouTube video ID.
  2. Process:
    • Scrapes comments associated with the provided video ID.
    • Standardizes comments to English.
    • Performs sentiment analysis using the chosen model.
    • Computes sentiment trends over the specified time frame.
  3. Output: Presents sentiment trends graphically, offering insights into sentiment dynamics.

Live Demo: https://sentimentt-analysis.streamlit.app/

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This repository offers a solution to analyze sentiments for a specified YouTube video.

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