  Sentiment Analysis is currently a vital area of research. With the
advancement in the use of the internet, the creation of social media, websites,
blogs, opinions, ratings, etc. has increased rapidly. People express their
feedback and emotions on social media posts in the form of likes, dislikes,
comments, etc. The rapid growth in the volume of viewer-generated or
user-generated data or content on YouTube has led to an increase in YouTube
sentiment analysis. Due to this, analyzing the public reactions has become an
essential need for information extraction and data visualization in the
technical domain. This research predicts YouTube Ad view sentiments using Deep
Learning and Machine Learning algorithms like Linear Regression (LR), Support
Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and Artificial
Neural Network (ANN). Finally, a comparative analysis is done based on
experimental results acquired from different models.
