Sentiment Analysis and Opinion Mining

(Introduction and Survey)

New Book, Bing Liu, Morgan & Claypool Publishers, May 2012 (165 pages)
Synthesis Lectures on Human Language Technologies

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis.

Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations.

Teaching and Learning: This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining.

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167 Pages, May 2012.
Paperback: ISBN 9781608458844
eBook: ISBN 9781608458851
Get the draft here
If you need an evaluation copy for teaching, you can drop me an email also.

Table of Contents (full version) - (403 references)

  1. Chapter 1: Sentiment Analysis: A Fascinating Problem
    1.1 Sentiment Analysis Applications
    1.2 Sentiment Analysis Research
    1.3 Opinion Spam Detection
    1.4 What.s Ahead
  2. Chapter 2: The Problem of Sentiment Analysis
    2.1 Problem Definitions
    2.2 Opinion Summarization
    2.3 Different Types of Opinions
    2.4 Subjectivity and Emotion
    2.5 Author and Reader Standing Point
    2.6 Summary
  3. Chapter 3: Document Sentiment Classification
    3.1 Sentiment Classification Using Supervised Learning
    3.2 Sentiment Classification Using Unsupervised Learning
    3.3 Sentiment Rating Prediction
    3.4 Cross-Domain Sentiment Classification
    3.5 Cross-Language Sentiment Classification
    3.6 Summary
  4. Chapter 4: Sentence Subjectivity and Sentiment Classification
    4.1 Subectivity Classification
    4.2 Sentence Sentiment Classification
    4.3 Dealing with Conditional Sentences
    4.4 Dealing with Sarcastic Sentences
    4.5 Cross-language Subjectivity and Sentiment Classification
    4.6 Using Discourse Information for Sentiment Classification
    4.7 Summary
  5. Chapter 5: Aspect-based Sentiment Analysis
    5.1 Aspect Sentiment Classification
    5.2 Basic Rules of Opinions and Compositional Semantics
    5.3 Aspect Extraction
    5.4 Identifying Resource Usage Aspect
    5.5 Simutaneous Opinion Lexicon Expansion and Aspect Extraction
    5.6 Grouping Aspects into Categories
    5.7 Entity, Opinion Holder and Time Extraction
    5.8 Coreference Resolution and Word Sense Disambiguation
    5.9 Summary
  6. Chapter 6: Sentiment Lexicon Generation
    6.1 Dictionary-based Approach
    6.2 Corpus-based Approach
    6.3 Desirable and Undesirable Facts
    6.4 Summary
  7. Chapter 7: Opinion Summarization
    7.1 Aspect-based Opinion Summarization
    7.2 Improvements to Aspect-based Opinion Summarization
    7.3 Contrastive View Summarization
    7.4 Traditional Summarization
    7.5 Summary
  8. Chapter 8: Analysis of Comparative Opinions
    8.1 Problem Definitions
    8.2 Identify Comparative Sentences
    8.3 Identifying Preferred Entities
    8.4 Summary
  9. Chapter 9: Opinion Search and Retrieval
    9.1 Web Search vs. Opinion Search
    9.2 Existing Opinion Retrieval Techniques
    9.3 Summary
  10. Chapter 10: Opinion Spam Detection
    10.1 Types of Spam and Spamming
    10.2 Supervised Spam Detection
    10.3 Unsupervised Spam Detection
    10.4 Group Spam Detection
    10.5 Summary
  11. Chapter 11: Quality of Reviews
    11.1 Quality as Regression Problem
    11.2 Other Methods
    11.3 Summary
  12. Chapter 12: Concluding Remarks
  13. Bibliography (with 403 references)

Lecture Slides: PDF

  • This set of (215) slides has been used in a few tutorials at AAAI-2011, EACL-2012 and Sentiment Anlaysis Symposium 2012. But the book has much more content.
  • References: you can download the book references on the right.

You may be interested in the following links

Errata List

First Draft: by Bing Liu on May 24, 2012.