Sentiment Analysis and Opinion Mining
5
Preface
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, to a considerable degree, conditioned upon 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 not only true for individuals but
also true for organizations.
Opinions and its related concepts such as sentiments, evaluations, attitudes,
and emotions are the subjects of study of sentiment analysis and opinion
mining. The inception and rapid growth of the field coincide with those of
the social media on the Web, e.g., reviews, forum discussions, blogs, micro-
blogs, Twitter, and social networks, because for the first time in human
history, we have a huge volume of opinionated data recorded in digital
forms. Since early 2000, sentiment analysis has grown to be one of the most
active research areas in natural language processing. It is also widely studied
in data mining, Web mining, and text mining. In fact, it has spread from
computer science to management sciences and social sciences due to its
importance to business and society as a whole. In recent years, industrial
activities surrounding sentiment analysis have also thrived. Numerous
startups have emerged. Many large corporations have built their own in-
house capabilities. Sentiment analysis systems have found their applications
in almost every business and social domain.
The goal of this book is to give an in-depth introduction to this fascinating
problem and to present a comprehensive survey of all important research
topics and the latest developments in the field. As evidence of that, this book
covers more than 400 references from all major conferences and journals.
Although the field deals with the natural language text, which is often
considered the unstructured data, this book takes a structured approach in
introducing the problem with the aim of bridging the unstructured and
structured worlds and facilitating qualitative and quantitative analysis of
opinions. This is crucial for practical applications. In this book, I first define
the problem in order to provide an abstraction or structure to the problem.
From the abstraction, we will naturally see its key sub-problems. The
subsequent chapters discuss the existing techniques for solving these sub-
problems.
This book 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
