YouTube Trending Videos

Motivation

YouTube has become one of the most popular worldwide video sharing platform nowadays. It includes videos varying from music videos to makeup tutorials, from lifestyle vlogs to education videos… YouTube seem be be a hub of creativity and informations. To organize these videos, they are required to be put into cateogries when uploaded. Choosing the approriate category can be important in increasing views through exposing to the right audiences. This project focuses on discovering what are the differences among YouTube video categories. This can help users to better understand these categories and make better decisions when deciding on choosing categories.

Data Source

For this project, the dataset used is found at Kaggle published by Mitchell J, a software developer at Backbeat Technologies. The version this project based on is version 115. The following is a weblink to the Kaggle page of the dataset: Trending YouTube Video Statistics. The main dataset used in this project is USvideos.csv. The supporting dataset is US_category_id.json, which serves as a dictionary that match category id to category names. They are also attached in this github repo.

Language

All the graphs are plotted and attached in the R notebook file.