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Sentiment analysis = mining opinions, sentiments, and emotions /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Sentiment analysis/ Bing Liu.
Reminder of title:	mining opinions, sentiments, and emotions /
Author:	Liu, Bing.
Published:	Cambridge :Cambridge University Press, : 2015.,
Description:	367 p. :digital ; : 24 cm.;
Notes:	Title from publisher's bibliographic system (viewed on 05 Oct 2015).
Subject:	Natural language processing (Computer science) -
Online resource:	https://doi.org/10.1017/CBO9781139084789
ISBN:	9781139084789

Sentiment analysis = mining opinions, sentiments, and emotions /
Liu, Bing.

Sentiment analysismining opinions, sentiments, and emotions /[electronic resource] :Bing Liu. - Cambridge :Cambridge University Press,2015. - 367 p. :digital ;24 cm.

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

Machine generated contents note: 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.

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.

ISBN: 9781139084789Subjects--Topical Terms:

641811
Natural language processing (Computer science)

LC Class. No.: QA76.9.N38 / L58 2015

Dewey Class. No.: 006.312

Sentiment analysis = mining opinions, sentiments, and emotions /
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245 1 0 $a Sentiment analysis $h [electronic resource] : $b mining opinions, sentiments, and emotions / $c Bing Liu.
260 $a Cambridge : $b Cambridge University Press, $c 2015.
300 $a 367 p. : $b digital ; $c 24 cm.
500 $a Title from publisher's bibliographic system (viewed on 05 Oct 2015).
505 8 $a Machine generated contents note: 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.
520 $a 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.
650 0 $a Natural language processing (Computer science) $3 641811
650 0 $a Computational linguistics. $3 555811
650 0 $a Public opinion $x Data processing. $3 1051089
650 0 $a Data mining. $3 528622
856 4 0 $u https://doi.org/10.1017/CBO9781139084789