Sentiment Analysis of twitter data Using Deep Learning Sentiment Analysis is a technique widely used in text mining. Twitter Sentiment Analysis, therefore means, using advanced text mining techniques to analyze the sentiment of the text (here, tweet) in the form of positive, negative and neutral. It is also known as Opinion Mining, is primarily for analyzing conversations, opinions, and sharing of views (all in the form of tweets) for deciding business strategy, political analysis, and also for assessing public actions.

Enginuity, Revealed Context, Steamcrab, MeaningCloud, and SocialMention are some of the well-known tools used for the analysis of Twitter sentiment. R and Python are widely used for sentiment analysis dataset twitter. Sentiment Analysis of Twitter data is now much more than a college project or a certification program. A good number of Tutorials related to Twitter sentiment are available for educating students on the Twitter sentiment analysis project report and its usage with R and Python. You may also enroll for a python tutorial for the same program to get a promising career in sentiment analysis dataset twitter.