Sentimental Analysis with/without Natural Language Processing

We live in the era where majority of the population resorts to social media platforms to get their daily digest of news, entertainment, livelihoods, etc. YouTube is one such social media platform that hosts majority of the population. YouTube attracts lot of eyes when it comes to provide entertainment, news, etc. The issue with this platform is that the majority of the population is unconsciously consuming biased media content and it only gets worse when we know the reality that there is no mechanism in existence that addresses this problem. Through this project we aim to address this issue. Our focus is to build a mechanism that leverages the power of modern computing advances i.e., Machine Learning to come up with a model that performs a sentiment analysis of the content.  Sentiment analysis refers to the field of analyzing and evaluation of – opinions, sentiments, attitudes, and emotions of users via scrutinizing media content posted on social media. The analysis is performed in real time so that any user who is consuming some content on YouTube gets an idea that whether the content being played is biased or not, whether the content can hurt other individual sentiments or is neutral.