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
9 - Opinion Summarization and Search
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
As discussed in Chapter 2, in most sentiment analysis applications, one needs to study opinions from many people; due to the subjective nature of opinions, looking at only the opinion from a single person is usually not sufficient. To understand a large number of opinions, some form of summary is necessary. Definition 2.10 in Chapter 2 defined a structured opinion summary called aspect-based summary, also known as feature-based summary in the reports by Hu and Liu (2004) and Liu et al. (2005). Much of the opinion summarization research is based on this definition. This form of summary is also widely used in industry. For example, both Microsoft Bing and Google Product Search use aspect-based summary in their opinion analysis systems.
- Type
- Chapter
- Information
- Sentiment AnalysisMining Opinions, Sentiments, and Emotions, pp. 259 - 272Publisher: Cambridge University PressPrint publication year: 2020