Text Mining and Sentimental Analysis on Comments using Machine Learning and NLP

Abstract

Now-a-days video streaming platforms like YouTube, twitch on-line etc. but the downside comes with the quantity of users and big information that is been generated through comments, truth essence of technology engineering is finding real-life problems. Throughout this project, we have a tendency to tend to creating associate algorithmic rule that collects and analyses the comments in glorious internet websites like Facebook, YouTube and various platforms. We have a tendency to tend to perform a sentimental analysis and word frequency over the collected information. There square measure some ways that to urge the output like internet extensions or an online web site. That the account holders will have a firm and clear arrange that viewers ought to expresses with relevance the content that is been uploaded by the admin. With the help of Python methodology like Scraping, the data collected from the comments square measure analyzed and final results square measure provided. For this project YouTube is been elite as a result of the bottom platform for development and aggregation information required as a result of it holds the foremost vital shopper or shopper information at intervals the kind of channel admins and viewer.