-We are using Youtube API V3 to collect data

-Resulted csv files of Music,Sports and News will be used as input

-Input Variables :Video id,text display,text original,user name,video url,channel url, channel name,no of likes and ratings,Output Variables :Positive,Negative and Neutral

-Data wrangling techniques will be used to clean and transform the data

-To use sentiment analysis/text analysis technique to determine whether the users comments are a positive, negative or neutral and whether comments are parallel with the content they are watching

-In online video platform youtube is the primary choice for everyone and having a wide audience thousands of videos and comments are uploaded every minute

-We will understand the sentiments expressed in comments to see how they will effect the brand

-To execute Natural Language Processing for classification of comments as positive, negative or neutral

-Visualization techniques like ggplots will be use to analyse the data

-Based on predicted models accuracy for different data sets we will predict the best model

-Our evaluation will also include whether our data is biased towards positive, negative or neutral sentiments.