Sentiment analysis and opinion mining are closely related but have slight differences in their focus and scope.

  Sentiment analysis refers to the process of determining and classifying the sentiment or emotional tone expressed in a piece of text, such as positive, negative, or neutral. It involves analyzing the subjective information contained in the text and understanding the writer's attitude or opinion towards a particular topic or entity.

  On the other hand, opinion mining, also known as opinion extraction or opinion retrieval, involves extracting and summarizing people's opinions, evaluations, or beliefs about a specific subject or entity. It aims to uncover not only the sentiment but also the specific aspects, attributes, or features that are being discussed or evaluated. It involves identifying and categorizing subjective information in the text, such as opinions, sentiments, and emotions, along with the associated topic or entity.

  In summary, sentiment analysis focuses primarily on understanding sentiment (positive, negative, or neutral), while opinion mining goes beyond sentiment to capture specific aspects and features associated with opinions and evaluations. Sentiment analysis is essentially a subset or component of opinion mining, which provides a more comprehensive understanding of people's opinions and attitudes.