Skip to search
Skip to main content
Title starts with
Author (sorted by title)
Call number (browse)
Princeton University Library Catalog
Sentiment Analysis and Opinion Mining [electronic resource] / by Bing Liu.
1st ed. 2012.
Cham : Springer International Publishing : Imprint: Springer, 2012.
1 online resource (XIV, 167 p.)
Natural language processing (Computer science).
Synthesis Lectures on Human Language Technologies,
[More in this series]
Synthesis Lectures on Human Language Technologies, 1947-4059
[More in this series]
Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online. Table of Contents: Preface / Sentiment Analysis: A Fascinating Problem / The Problem of Sentiment Analysis / Document Sentiment Classification / Sentence Subjectivity and Sentiment Classification / Aspect-Based Sentiment Analysis / Sentiment Lexicon Generation / Opinion Summarization / Analysis of Comparative Opinions / Opinion Search and Retrieval / Opinion Spam Detection / Quality of Reviews / Concluding Remarks / Bibliography / Author Biography.
Sentiment Analysis: A Fascinating Problem
The Problem of Sentiment Analysis
Document Sentiment Classification
Sentence Subjectivity and Sentiment Classification
Aspect-Based Sentiment Analysis
Sentiment Lexicon Generation
Analysis of Comparative Opinions
Opinion Search and Retrieval
Opinion Spam Detection
Quality of Reviews
Show 12 more Contents items
Statement on language in description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
Ask a Question
Suggest a Correction
Report Harmful Language