Book contents
- Sentiment Analysis
- Studies in Natural Language Processing
- Sentiment Analysis
- Copyright page
- Contents
- Preface
- Acknowledgments
- 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 Intent
- 12 Detecting Fake or Deceptive Opinions
- 13 Quality of Reviews
- 14 Conclusion
- Appendix
- Bibliography
- Index
2 - The Problem of Sentiment Analysis
Published online by Cambridge University Press: 23 September 2020
- Sentiment Analysis
- Studies in Natural Language Processing
- Sentiment Analysis
- Copyright page
- Contents
- Preface
- Acknowledgments
- 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 Intent
- 12 Detecting Fake or Deceptive Opinions
- 13 Quality of Reviews
- 14 Conclusion
- Appendix
- Bibliography
- Index
Summary
In this chapter, we define an abstraction of the sentiment analysis problem. This abstraction gives us a statement of the problem and enables us to see a rich set of interrelated subproblems. It is often said that if we cannot structure a problem, we probably do not understand the problem. The objective of the definitions is thus to abstract a structure from the complex and intimidating unstructured natural language text. This structure serves as a common framework to unify various existing research directions and enable researchers to design more robust and accurate solution techniques by exploiting the interrelationships of the subproblems. From a practical application point of view, the definitions let practitioners see which subproblems need to be solved in building a sentiment analysis system, how the subproblems are related, and what output should be produced.
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- Chapter
- Information
- Sentiment AnalysisMining Opinions, Sentiments, and Emotions, pp. 18 - 54Publisher: Cambridge University PressPrint publication year: 2020
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