This manual pertains to the comprehensive study of sentiment analysis and opinion mining, a field dedicated to understanding human evaluations, attitudes, and emotions expressed in written language. It delves into the core concepts and cutting-edge advancements within this rapidly evolving area of natural language processing and data mining. The book serves as an introductory and survey text, suitable for students, researchers, and practitioners interested in analyzing opinions from various sources, particularly social media.
The manual covers a wide array of critical topics, including document and sentence-level sentiment classification, aspect-based sentiment analysis, opinion summarization, and the detection of opinion spam. It is designed to equip readers with the knowledge and tools necessary to navigate the complexities of opinionated data, making it an invaluable resource for those engaged in social media analysis, text mining, and data mining. Lecturers will find it a useful text for courses in natural language processing and related disciplines.
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
Author: Liu, Bing
Publisher: Morgan & Claypool Publishers
Illustration: n
Language: ENG
Title: Sentiment Analysis and Opinion Mining
Pages: 00000 (Encrypted EPUB) / 00000 (Encrypted PDF)
On Sale: 2012-05-01
SKU-13/ISBN: 9781608458844
Category: Computers : Natural Language Processing
Category: Computers : Social Aspects - General
Category: Computers : Database Management - Database Mining
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
Author: Liu, Bing
Publisher: Morgan & Claypool Publishers
Illustration: n
Language: ENG
Title: Sentiment Analysis and Opinion Mining
Pages: 00000 (Encrypted EPUB) / 00000 (Encrypted PDF)
On Sale: 2012-05-01
SKU-13/ISBN: 9781608458844
Category: Computers : Natural Language Processing
Category: Computers : Social Aspects - General
Category: Computers : Database Management - Database Mining
