Sentiment Analysis and Opinion Mining: Synthesis Lectures on Human Language Technologies

Sentiment Analysis and Opinion Mining: Synthesis Lectures on Human Language Technologies

Bing Liu

Source: University of Illinois Chicago

Sentiment Analysis and Opinion Mining (2012) by Bing Liu explains how computers can automatically identify and analyze opinions, feelings, and attitudes expressed in text. The book focuses on understanding whether people express positive, negative, or neutral views about products, services, events, or issues, especially in sources like online reviews, social media, blogs, and forums. It discusses the main tasks in sentiment analysis, such as analyzing sentiment at the document, sentence, and aspect level, identifying opinion targets, summarizing large numbers of opinions, and detecting misleading or fake reviews. The book also explains common techniques used in the field, including machine learning methods and sentiment lexicons, as well as the challenges involved, such as ambiguous language and context. Overall, the book provides a clear overview of how opinion data can be extracted from text and why this is important for research, business, and social analysis.

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