
Sentiment Analysis
mining opinions, sentiments, and emotions
$243.89
- Hardcover
448 pages
- Release Date
15 October 2020
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 |
You Can Find This Book In
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.
Returns
This item is eligible for free returns within 30 days of delivery. See our returns policy for further details.




