Sentiment analysis is an NLP technique that automatically determines the emotional polarity (positive, negative, or neutral) of text. It is also known as opinion mining.

Approaches are broadly divided into rule-based (using sentiment lexicons) and machine learning-based (using deep learning models like BERT). Zero-shot sentiment analysis using LLMs is also gaining attention. Sentiment analysis and ML books cover these methods in detail.

Business applications include social media monitoring, product review aggregation, brand monitoring, and customer support prioritization.

Sentiment analysis in Japanese is challenging due to sarcasm, indirect expressions, and the importance of context. Practical text analytics guides address language-specific challenges.