ramtiin/Predicting-YouTube-Dislikes-using-Machine-Learning
I used Catboost for training a model on the numerical features of every YouTube video (e.g., the number of views, comments, likes, etc.) along with sentiment analysis of the video descriptions and comments using the VADER sentiment analysis model.
This project helps YouTube creators, marketers, or data analysts understand the potential reception of a video before or shortly after it's published. By analyzing a video's numerical metrics like views and comments, alongside the sentiment within its description and comments, it predicts the likely number of dislikes. This allows content creators and strategists to gauge audience reaction and refine their content approach.
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Use this if you are a YouTube content creator, marketer, or data analyst looking to anticipate audience sentiment and potential dislikes for your videos based on available data.
Not ideal if you need to predict dislikes based on video content itself (e.g., visual or audio elements) rather than text and numerical metadata.
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Mar 27, 2022
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