Sentimental Analysis with and without NLTK

Sentiment Analysis is an NLP (Natural Language Processing) technique that is used to interpret the emotion behind the text. We will be able to predict if the emotion is Positive, Negative, or Neutral. Ex. Amazon: customer reviews about the product. Twitter comments help to know the majority of views. The goal of this report is to give an introduction to this fascination project and to present a framework which will perform sentiment on sentences to analysis the NLP by associating using rule based technique and naïve bayes. In today’s era, every social media and app has widely increased data that is getting added exponentially. Every individual has their own set of information and views. To know the views about the most trending topics from a widely growing user. In this paper, we have discussed and tried to make a model based on natural language processing. Here we have discussed the two methods, that is the method using a tool kit and the method without using a tool kit. Both the methods have their own model that will work on training the set of views and words given by the user. The goal of this report is to give an introduction to this fascination project and to present a framework which will perform sentiment on sentences to analysis the NLP by associating using rule based technique and naïve bayes