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Youtube Data Analysis with YT API

View Jupyter notebook on NBViewer- https://nbviewer.org/github/Rohit2350/YTAPI-Analysis/blob/main/Youtube%20Analysis.ipynb

Summary

    -Analyzed video data from 9 popular Data Science/Analytics YouTube channels.
    -Investigated correlations between video performance (views, likes, comments) and engagement metrics.

Key Findings:

    -Higher likes and comments correlate with more views; likes serve as a stronger engagement indicator.
    -Most-viewed videos have titles with 30-70 characters and include 5-30 tags.
    -Mondays and Fridays are the most popular days for video uploads, while Sundays are less favored.
    -Comment sentiment is generally positive, with potential market gaps in requested content.
    -Future Research: Further analysis of comment sentiment, video thumbnails, posting times, and causal relationships in video engagement.

About

Analyzed data from 9 Data Science/Analytics YouTube channels, revealing that higher likes and comments correlate with more views. Most-viewed videos have titles of 30-70 characters and 5-30 tags. Uploads peak on Mondays and Fridays, while comment sentiment is generally positive, highlighting potential content gaps.

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