Social Media Sentiment Analysis Using Twitter Datasets - DataScienceCentral.com

Several hundreds of thousands of raw data files are uploaded by users every day to social media sites. Online user data provides access to an enormous amount of information regarding products, services, places, and events, which makes it suitable for sentiment analysis. Valuable information can be extracted by analyzing the sentiment of the data. It is a method for interpreting opinions within a text that uses Natural Language Processing (NLP) to extract positive, negative, and natural meanings from user-generated content shared on social media platforms. Sentiment analysis has been previously applied to products or movie reviews to understand customers' interests better and, thus, improve outcomes and service offerings.