Sentiment Analysis and Opinion Mining

by Bing Liu

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.

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. Lecture slides are also available online.

Table of Contents: Preface / Sentiment Analysis: A Fascinating Problem / The Problem of Sentiment Analysis / Document Sentiment Classification / Sentence Subjectivity and Sentiment Classification / Aspect-Based Sentiment Analysis / Sentiment Lexicon Generation / Opinion Summarization / Analysis of Comparative Opinions / Opinion Search and Retrieval / Opinion Spam Detection / Quality of Reviews / Concluding Remarks / Bibliography / Author Biography

Genres: Nonfiction, Artificial Intelligence

180 pages, Kindle Edition

First published May 1, 2012

Reviews

[VastEdge Inc. · Rating 4 out of 5]

Sentiment analysis plays a vital role in enabling the businesses to work actively on improving their visibility across the targeted websites and gain an in-depth insight of the buyer’s feedback about their product. Sentiment analysis of a guest’s data encourages the marketing players to evaluate the text in a way that exposes the valuable checkpoints and support them to take their visitor communication experience to the next level. It involves computational study of behavior of an individual in terms of his buying interest and then mining his opinions about a company’s business entity. This entity can be visualized as an event, individual, blog post or product experience.

While there happens to be lot of noise in the arena of digital marketing, companies find it difficult to listen to the real voice of their customers. Though, a data-driven marketing strategy often results in successful campaigns for brand publicity on target social media websites, yet to easily capture the ever-shifting pulse of a reader’s interest, a digital marketing team must be able to analyze the 360 insights of their guests’ voice.

Sentiment Analysis in Advertisement Marketing:
Nowadays, digital world is occupied with numerous social networking websites that the enterprises use post their ads and build a strong online presence. The sole objective of the engaged marketers and research analysts in these companies is to increase the buying motivation of massive internet savvy shoppers and steer an impulse to purchase their products. While opinion mining extricates the guest’s opinions, sentiment analysis helps in identifying the core sentiments of the guests that they have expressed in the form of a comment or re-tweet.

Sentiment Analysis in Business Intelligence:
Sentiment analysis is in high demand for its greater efficiency in handling the text documents for entity behavior analytics. On account of its capability to deliver accurate results for natural language processing, businesses are incorporating text sentiment analysis into their routine processes. Many big companies who are compassionate to score high in influence attribution are using this powerful gauging tool to improve their business intelligence in finance, healthcare, SaaS, big data and IoT.

Sentiment Analysis in Social Media Marketing:
Text sentiment analysis in market surveys, social media monitoring, twitter hash tag and RSS feed analysis; is oriented towards extracting the opinions, looking out for the sentiments expressed in the text and then classifying the grapple between opinions to detect the ratio of polarity. Many travel booking companies and luxury hoteliers have adopted this mechanism to boost the magnitude of their website reviews and generate higher revenues by driving more direct customers to avail their services.

[Rufina · Rating 5 out of 5]

Slay bing liu. Concise and clear!

[Tarek Amr · Rating 2 out of 5]

The main problem with this book is its shallowness. The author describes interesting topics in each chapter, but he only gives you a brief introduction and points you to the research papers written in those topics, and that's it. I do take notes of the research papers I want to read in Evernote to read them later, and this book is not any better that my Evernotesque bookmarks. Well, may be it just saved me from writing down the papers names myself, and wrote them for me instead, yet, I still have to read the papers themselves to understand what he is talking about how the Sentiment Analysis and Opinion Mining problems are really solved.

[Dani · Rating 3 out of 5]

There isnt much out there in the way of Sentiment Analysis, but Liu is a reputable person in the field. It was occasionally murky to read for those of us who dont know computational linguistic lingo, but is otherwise informative. Learned more from this text than I did from the professor teaching the class anyway.

[c-lOw · Rating 5 out of 5]

Great introductory book to Sentiment Analysis. Contains a lot of references. Great for academic research.