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Sentiment analysis : mining opinions, sentiments, and emotions / Bing Liu, University of Illinois at Chicago.

By: Material type: TextTextLanguage: English Cambridge : Cambridge University Press, 2015Description: 1 online resource (367 pages) : digital, PDF file(s)Content type:
  • text
Media type:
Carrier type:
  • online resource
ISBN:
  • 9781139084789 (ebook)
Subject(s): Additional physical formats: No titleDDC classification:
  • 006.3/12
LOC classification:
  • QA76.9.N38 L58 2015
Online resources: Summary: 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.
List(s) this item appears in: Computer Science
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Item type Current library Call number URL Status Barcode
E-Book E-Book Ranganathan Library 6.312 (Browse shelf(Opens below)) Link to resource Available E01853

Title from publisher's bibliographic system (viewed on 05 Oct 2015).

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.

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