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Sentiment analysis : = mining opinions, sentiments, and emotions /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Sentiment analysis :/ Bing Liu, University of Illinois at Chicago.
Reminder of title:	mining opinions, sentiments, and emotions /
Author:	Liu, Bing,
Description:	1 online resource (367 pages) :digital, PDF file(s). :
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 (ebook)

Sentiment analysis : = mining opinions, sentiments, and emotions /
Liu, Bing,1963-

Sentiment analysis :mining opinions, sentiments, and emotions /Bing Liu, University of Illinois at Chicago. - 1 online resource (367 pages) :digital, PDF file(s).

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: 9781139084789 (ebook)Subjects--Topical Terms:

641811
Natural language processing (Computer science)

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

Dewey Class. No.: 006.3/12

Sentiment analysis : = mining opinions, sentiments, and emotions /
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245 1 0 $a Sentiment analysis : $b mining opinions, sentiments, and emotions / $c Bing Liu, University of Illinois at Chicago.
264 1 $a Cambridge : $b Cambridge University Press, $c 2015.
300 $a 1 online resource (367 pages) : $b digital, PDF file(s).
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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
776 0 8 $i Print version: $z 9781107017894
856 4 0 $u https://doi.org/10.1017/CBO9781139084789