Sentiment analysis : mining opinions, sentiments, and emotions
著者
書誌事項
Sentiment analysis : mining opinions, sentiments, and emotions
（Studies in natural language processing）
Cambridge University Press, 2020
2nd ed
- : hardback
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注記
Includes bibliographical references (p. 376-425) and index
Previous ed.: 2015
内容説明・目次
内容説明
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.
目次
- 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.
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