Twitter has been called the "global town square" recently by billionarie Elon Musk as he tries to purchase the company for $43B. Musk is eluding to the vast amount of users the platform has, 330 million and growing, which all have a voice.
Businesses can tap into this vast user base to discover new trends, imtimately understand customers' perceptions of thiers and their competitors products and services, as well as be able to have a good understanding of who their customers are.
The challenge, however, is that there's so much information being shared on the platform it's difficult to synthesize it all as well as for brands to quickly detect negative social mentions that could harm their business.
This project undertakes the opportunity to analyze sentiment of each major U.S. airline using data from Twitter scrapped from 2015. A multi category classification analysis follows using NLP to categorize sentiment from tweets into positive, negative and neutral.