Academy & Industry Research Collaboration Center (AIRCC)

Volume 11, Number 08, June 2021

Data-Driven Intelligent Application for Youtube Video Popularity Analysis
using Machine Learning and Statistics


Wenxi Gao1, Ishmael Rico2 and Yu Sun3, 1University of Toronto, Canada, 2University of California, USA, 3California State Polytechnic University, USA


People now prefer to follow trends. Since the time is moving, people can only keep themselves from being left behind if they keep up with the pace of time. There are a lot of websites for people to explore the world, but websites for those who show the public something new are uncommon. This paper proposes an web application to help YouTuber with recommending trending video content because they sometimes have trouble in thinking of the video topic. Our method to solve the problem is basically in four steps: YouTube scraping, data processing, prediction by SVM and the webpage. Users input their thoughts on our web app and computer will scrap the trending page of YouTube and process the data to do prediction. We did some experiments by using different data, and got the accuracy evaluation of our method. The results show that our method is feasible so people can use it to get their own recommendation.


Machine Learning, data processing, SVM, topic prediction.