Natural Language Processing
Twitter possesses 330 million monthly active users, which allows businesses to reach a broad population and connect with customers without intermediaries. On the other hand, there’s so much information that it’s difficult for brands to quickly detect negative social mentions that could harm their business.
That's why sentiment analysis/classification, which involves monitoring emotions in conversations on social media platforms, has become a key strategy in social media marketing.
Listening to how customers feel about the product/service on Twitter allows companies to understand their audience, keep on top of what’s being said about their brand and their competitors, and discover new trends in the industry.
A sentiment analysis job about the problems of each major U.S. airline. Twitter data was scraped from February of 2015 and contributors were asked to first classify positive, negative, and neutral tweets, followed by categorizing negative reasons (such as "late flight" or "rude service").