We train a Naive Bayes classifier to predict sentiment from thousands of Twitter tweets. This project could be practically used by any company with social media presence to automatically predict customer's sentiment (i.e.: whether their customers are happy or not). The process could be done automatically without having humans manually review thousands of tweets and customer reviews.
We will be using Natural Language Processing or it's called NLP in short. to analyse emotions and sentiments of given text. In this project we will be able to:
- analyse different emotions present in a tweet like sadness, happiness, jealousy etc
- You will be able to find out the dominant emotion in the text
- You will be able to plot those emotions on a graph
- And you will also be able to tell whether the whole text is a positive or negative emotion
- 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.