Sentiment Analysis, 9781108486378
Hardcover
Unlock hidden feelings: Analyze opinions, emotions, and attitudes using language.

Sentiment Analysis

mining opinions, sentiments, and emotions

$243.89

  • Hardcover

    448 pages

  • Release Date

    15 October 2020

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Summary

Unlocking Emotions: A Deep Dive into Sentiment Analysis

Sentiment analysis is the computational study of people’s opinions, sentiments, emotions, moods, and attitudes. This fascinating problem offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis.

This comprehensive introduction to the topic takes a natural-language-processing point of view to help readers understand the underlying structure of the…

Book Details

ISBN-13:9781108486378
ISBN-10:1108486371
Author:Bing Liu
Publisher:Cambridge University Press
Imprint:Cambridge University Press
Format:Hardcover
Number of Pages:448
Edition:2nd
Release Date:15 October 2020
Weight:780g
Dimensions:240mm x 159mm x 27mm
Series:Studies in Natural Language Processing
What They're Saying

Critics Review

‘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, Chinese Academy of Sciences

About The Author

Bing Liu

Bing Liu is a distinguished professor of Computer Science at the University of Illinois at Chicago. His current research interests include sentiment analysis, lifelong machine learning, natural language processing, and data mining. He has published extensively in top conferences and journals, and his research has been cited on the front page of the New York Times. Three of his research papers also received Test-of-Time awards. He is the recipient of ACM SIGKDD Innovation Award in 2018, and is a Fellow of the ACM, AAAI, and IEEE. He served as the Chair of ACM SIGKDD from 2013-2017.

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