Sentiment Analysis
Definition
An NLP technique that identifies and extracts subjective information from text, determining whether the expressed opinion is positive, negative, or neutral.
Sentiment analysis is one of the most widely deployed NLP applications in business. It automatically processes customer reviews, social media posts, survey responses, and support tickets to gauge public opinion and customer satisfaction. Modern approaches range from fine-tuned BERT models for high accuracy to zero-shot classification using large language models. Beyond simple positive/negative classification, advanced systems detect specific emotions (joy, anger, frustration), aspect-based sentiment (sentiment toward specific product features), and sarcasm. Applications include brand monitoring, stock market prediction (analyzing financial news sentiment), product feedback analysis, and political opinion polling. Challenges include handling sarcasm, context-dependent language, and cultural nuances in expression.
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