Book contents
- Frontmatter
- 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 Intentions
- 12 Detecting Fake or Deceptive Opinions
- 13 Quality of Reviews
- 14 Conclusions
- Appendix
- Bibliography
- Index
10 - Analysis of Debates and Comments
Published online by Cambridge University Press: 05 June 2015
- Frontmatter
- 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 Intentions
- 12 Detecting Fake or Deceptive Opinions
- 13 Quality of Reviews
- 14 Conclusions
- Appendix
- Bibliography
- Index
Summary
Opinion documents come in many different forms. So far, we have implicitly assumed that individual documents are independent of each other or have no relationships. In this chapter, we move on to two social media contexts that involve extensive interactions of their participants, that is, debates/discussions and comments, which are also full of expressions of sentiments and opinions. However, the key characteristic of the documents in such media forms is that they are not independent of each other, which is in contrast to standalone documents such as reviews and blog posts. Interactive exchanges of discussions among participants make these media forms much richer for analysis. The interactions can be seen as relationships or links among participants and also among posts. Thus, we not only can perform sentiment analysis as we have discussed in previous chapters, but also carry out additional types of analyses that are characteristic of interactions, for example, grouping people into camps, discovering contentious issues of debates, mining agreement and disagreement expressions, discovering pairwise arguing nature, and so on. Because debates are exchanges of arguments and reasoning among participants who may be engaged in some kind of deliberation to achieve a common goal, it is interesting to study whether each participant in online debate forums indeed gives reasoned arguments with justifiable claims via constructive debates or just exhibits dogmatism and egotistic clashes of ideologies. These tasks are important for many fields of social science such as political science and communications. Central to these tasks are the sentiment of agreement and disagreement, which are instrumental to these analyses. These additional types of analyses are the focus of this chapter.
Comments are posts that comment on online articles (e.g., news articles, blog posts, and reviews), videos, images, and so on. We use comments about online articles in our study in this chapter. Comments typically contain many types of information, for example, views and opinions from the readers of the article about the article and/or its subject matter, questions to the author of the article or to other readers, and discussions among readers and between readers and the author of the article.
- Type
- Chapter
- Information
- Sentiment AnalysisMining Opinions, Sentiments, and Emotions, pp. 231 - 249Publisher: Cambridge University PressPrint publication year: 2015