國立虎尾科技大學 |

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

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Sentiment analysis :/ Bing Liu, University of Illinois at Chicago.
其他題名:	mining opinions, sentiments, and emotions /
作者:	Liu, Bing,
面頁冊數:	1 online resource (367 pages) :digital, PDF file(s). :
附註:	Title from publisher's bibliographic system (viewed on 05 Oct 2015).
標題:	Data mining. -
電子資源:	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:

528622
Data mining.

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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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.
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