Emotion & Sentiment Analysis with/without NLTK using Python

Welcome to this new video series in which we will be using Natural Language Processing or it's called NLP in short. to analyse emotions and sentiments of given text. After completing this videos series - 1) You will be able to analyse different emotions present in an essay like sadness, happiness, jealousy etc 2) You will be able to find out the dominant emotion in the text 3) You will be able to plot those emotions on a graph 4) And you will also be able to tell whether the whole text is a positive or negative emotion 5) And finally you will also be able scrap tweets with a hashtag and find out the public opinion on that hashtag. For example you can search for #donaldtrump and find out whether that emotion is associated with a positive or a negative sentiment. First we will be doing all the natural language processing and sentiment analysis on our own without the use of a library or a package. So that you guys properly understand the concepts of NLP and then we can go on to use NLTK library to shorten our work.

In this video we will be creating our new Project and also installing Python and Pycharm.

All right guys! Welcome back. In this video we are going to learn how to clean the text before we can apply our natural language processing concepts on it. Cleaning is done in two main ways. Making sure everything is in lowercase and secondly we remove all the unwanted characters from it like punctuations. But even before that we need to read text in our python program. We need to convert it to lowercase because the words are the soul of analyzing text. And when we compare words in natural language processing a word like an Apple with a capital A, is not equal to the same word in small case, for example an apple with a small 'a'. Therefore to compare words we need to make sure the entire text which we are going to be analyzing is in lower case. This is will make more sense as we go further along the videos.