“Super Trending” - A Trending YouTube Video that obtains over a million views within a 24-hour time period.
Given recent times with the ongoing pandemic, content creators on YouTube may notice a gain of a larger audience as people look for things to do within their free time. To take advantage of this, analyzing what exactly makes a video trend is important to creators when seeking out ways to increase views. This project attempts to predict the performance of videos such that they would go trending within a day of release. An equation was developed manually to separate videos into two classes: those that reach a million views or more within twenty-four hours, and those that do not. The category, title, tags, description, and the publish date were selected as features for the algorithm. Multiple machine learning algorithms were used to predict determine which gave the best performance. In doing so, Random Forest and the Decision Tree classifiers ended up giving the best results.
Install Dependencies.
pip install -r requirements
Launch the GUI.
python yt.py
https://www.kaggle.com/datasnaek/youtube-new
https://www.youtube.com/watch?v=2rJ86XD_bCw&feature=youtu.be