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Sentiment Analysis
Mining Opinions, Sentiments, and Emotions


  • Author: Bing Liu, University of Illinois, Chicago
  • Date Published: June 2015
  • availability: Available
  • format: Hardback
  • isbn: 9781107017894

£ 57.99

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About the Authors
  • 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.

    • 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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    Reviews & endorsements

    'As a whole, this book serves as a useful introduction to sentiment analysis along with in-depth discussions of linguistic phenomena related to sentiments, opinions, and emotions. Although many sentiment analysis methods are based on machine learning as in other NLP [Natural Language Processing] tasks, sentiment analysis is much more than just a classification or regression problem, because the natural language constructs used to express opinions, sentiments, and emotions are highly sophisticated, including sentiment shift, implicated expression, sarcasm, and so on. Liu has described these issues and problems very clearly. Readers will find this book to be inspiring and it will arouse their interests in sentiment analysis.' Jun Zhao, Computational Linguistics

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    Product details

    • Date Published: June 2015
    • format: Hardback
    • isbn: 9781107017894
    • length: 381 pages
    • dimensions: 240 x 160 x 24 mm
    • weight: 0.71kg
    • contains: 24 b/w illus. 9 tables
    • availability: Available
  • Table of Contents

    1. Introduction
    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.

  • Author

    Bing Liu, University of Illinois, Chicago
    Bing Liu is a Professor of Computer Science at the University of Illinois. His current research interests include sentiment analysis and opinion mining, data mining, machine learning, and natural language processing. He has published extensively in top conferences and journals, and his research has been cited on the front page of the New York Times. He is also the author of two books: Sentiment Analysis and Opinion Mining (2012) and Web Data Mining: Exploring Hyperlinks, Contents and Usage Data (1st edition, 2007; 2nd edition, 2011). He currently serves as the chair of ACM SIGKDD and is an IEEE Fellow.

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