Trending Pattern Identification of YouTube Gaming Channels Using Sentiment Analysis

Social media platforms play a vital role in business, entertainment, marketing, education, media, and communication. YouTube has become the most used platform for sharing videos in society due to its unique behavior. YouTube allows any person to create an account under any category of choosing to upload videos to be viewed by many millions of other people. This has become a trend among the entertainment industry hence it can easily reach to the users and gain popularity for the video materials hosted online. Many YouTube channel keepers are taking different actions to make the video popular. This research study aims at evaluating the comments provided by the users and identify their requirements and provide recommendations for the You Tubers to make their video popularized. The study has used sentiment analysis and feature extraction methods to derive the set of features required to concern in the development of YouTube videos. Hence the analysis discovers to most important trending videos related to user video types and shows up what are the most trending videos which the user will want to see. The study has used machine learning methods to analyze the trending features and identification of key recommendations for the users. This study has limited to the gaming videos posted in the YouTube channels.