Sentiment analysis: mining opinions, sentiments, and emotions
Material type:
TextSeries: Studies in natural language processingPublication details: Cambridge University Press 2020 CambridgeEdition: 2ndDescription: xvii, 431 p.: ill. Includes bibliographical references and indexISBN: - 9781108486378
- 006.312 L4S3-2020
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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Ahmedabad General Stacks | Non-fiction | 006.312 L4S3-2020 (Browse shelf(Opens below)) | Available | 203474 |
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| 006.312 E7C6 Confident data skills: master the fundamentals of working with data and supercharge your career | 006.312 I4I6 An introduction to text mining: research design, data collection, and analysis | 006.312 K9T3 Text mining in practice with R | 006.312 L4S3-2020 Sentiment analysis: mining opinions, sentiments, and emotions | 006.312 M6M2 Machine learning: algorithms and applications | 006.312 P2D2 Data science fundamentals for Python and Mongodb | 006.312 P3E9 Exploratory data analysis using R |
Table of content
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 Intents
12 Detecting Fake or Deceptive Opinions
13 Quality of Reviews
14 Conclusions
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 problem and the language constructs commonly used to express opinions, sentiments, and emotions. The book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. In addition to traditional computational methods, this second edition includes recent deep learning methods to analyze and summarize sentiments and opinions, and also new material on emotion and mood analysis techniques, emotion-enhanced dialogues, and multimodal emotion analysis.
. Data sets and slides available for instructors
. Covers state-of-the-art research techniques and practical algorithms to form the most comprehensive text on sentiment analysis
. Suitable for students, researchers and practitioners of computer science, management science, and social science
. Gives practitioners the necessary knowledge to build a practical sentiment analysis system
https://www.cambridge.org/in/academic/subjects/computer-science/artificial-intelligence-and-natural-language-processing/sentiment-analysis-mining-opinions-sentiments-and-emotions-2nd-edition?format=HB
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