Mining Opinions, Sentiments, and Emotions
$64.00 ( ) USD
- Author: Bing Liu, University of Illinois, Chicago
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Sentiment analysis is the computational study of people's opinions, sentiments, emotions, and attitudes. This fascinating problem is increasingly important in business and society. It offers numerous research challenges but promises insight useful to anyone interested in opinion analysis and social media analysis. This book gives a comprehensive introduction to the topic from a primarily natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs that are commonly used to express opinions and sentiments. It covers all core areas of sentiment analysis, includes many emerging themes, such as debate analysis, intention mining, and fake-opinion detection, and presents computational methods to analyze and summarize opinions. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences.Read more
- Covers state-of-the-art research techniques and practical algorithms to form the most comprehensive text on sentiment analysis
- Covers not only the core areas of sentiment analysis, but also several emerging topics such as debate, discussion and comment analysis, intention mining, and fake opinion detection
- Suitable for students, researchers and practitioners of computer science, management science, and social science
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- Date Published: May 2015
- format: Adobe eBook Reader
- isbn: 9781316308462
- contains: 24 b/w illus. 9 tables
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
2. The problem of sentiment analysis
3. Document sentiment classification
4. Sentence subjectivity and sentiment classification
5. Aspect sentiment classification
6. Aspect and entity extraction
7. Sentiment lexicon generation
8. Analysis of comparative opinions
9. Opinion summarization and search
10. Analysis of debates and comments
11. Mining intentions
12. Detecting fake or deceptive opinions
13. Quality of reviews.
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