How to use sentiment analysis on Twitter?
The internet age of today has changed the way consumers express their opinions and views. This is mainly carried out today via social media, product review websites, online forums, and blog posts among others. People nowadays are utilizing social media platforms such as Instagram, Facebook, and Twitter to share their views and express their opinions regarding their daily lives.
Sentiment analysis is s process that employs Natural Language Processing (NLP) to automate the mining of emotions, views, opinions, and attitude from database sources, tweets, speech, and texts. Sentiment analysis helps classify the views of consumers in categories such as neutral, negative, or positive.
Use of Sentiment Analysis on Twitter
Twitter consists of a large pool of data on feedbacks and reviews regarding varied fields such as political and social issues, products, brands, and entertainment among others. Hence, there is an ardent need for sentiment analysis, which can extrapolate the sentiments of consumers about a particular product or service.
Companies can also choose to employ sentiment analysis for trend prediction processes on Twitter. Tracking important sales data and public views or opinions can help organizations make informed decisions to achieve customer satisfaction.