Sentiment Analysis
Sentiment Analysis is a natural language processing technique used to determine the emotional tone or opinion expressed in text, such as whether a statement is positive, negative, or neutral.
What is Sentiment Analysis?
Sentiment analysis uses machine learning or language models to analyze text and identify the sentiment expressed by the writer. Depending on the system, it can classify text into categories such as positive, negative, and neutral, or detect more specific emotions such as anger, happiness, or frustration.
Why is Sentiment Analysis Important?
Sentiment analysis helps organizations understand opinions and reactions across large volumes of text without manually reviewing every message. It can reveal customer satisfaction, emerging concerns, and changes in public or user sentiment, supporting faster analysis and decision-making.
Common use cases
Sentiment Analysis is commonly used for customer feedback, social media monitoring, product reviews, market research, support tickets, and brand reputation analysis.