Sentiment Analysis

Sentiment analysis is the technology by which AI automatically identifies and classifies the emotions of a writer or speaker from text, audio, SNS posts, reviews, and similar sources. It primarily classifies the emotional polarity of content as "positive," "negative," or "neutral," visualizing the psychological state or reaction of the subject. By combining natural language processing (NLP) with machine learning techniques, it is possible to infer emotion from the context and vocabulary used in text. The latest models leveraging deep learning are even able to handle some degree of sarcasm and contextual ambiguity, enabling more sophisticated analysis. Primary use cases for sentiment analysis: • Aggregating and analyzing product reviews and surveys • Evaluating brand perception on SNS and detecting escalating negative sentiment • Evaluating customer service chats and voice calls • Supporting marketing strategy development • Measuring internal engagement and employee satisfaction As an "AI that listens to the genuine voice of customers" and helps companies understand them in order to build better products and services, sentiment analysis is being adopted across a wide range of industries.

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