What is sentiment analysis primarily used for?

Sentiment analysis is primarily used for determining the emotional tone in communication. This technique involves analyzing text data—such as social media posts, reviews, or other forms of written communication—to identify and categorize the feelings expressed by the author. By leveraging natural language processing (NLP) and machine learning algorithms, sentiment analysis can classify sentiments as positive, negative, or neutral, which is invaluable for understanding public opinion, customer feedback, and overall emotional engagement with content.

The application of sentiment analysis is widespread in areas like market research, customer service, and social media monitoring, where understanding the underlying emotional responses helps organizations tailor their strategies, products, or services to better meet the needs and preferences of their audience.