Opinion Mining and Sentiment Analysis

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Author :
Release : 2008
Genre : Data mining
Kind :
Book Rating : 503/5 ( reviews)

Opinion Mining and Sentiment Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Opinion Mining and Sentiment Analysis write by Bo Pang. This book was released on 2008. Opinion Mining and Sentiment Analysis available in PDF, EPUB and Kindle. This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems.

Sentiment Analysis and Opinion Mining

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Author :
Release : 2022-05-31
Genre : Computers
Kind :
Book Rating : 452/5 ( reviews)

Sentiment Analysis and Opinion Mining - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Sentiment Analysis and Opinion Mining write by Bing Liu. This book was released on 2022-05-31. Sentiment Analysis and Opinion Mining available in PDF, EPUB and Kindle. 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

Sentiment Analysis

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Author :
Release : 2020-10-15
Genre : Computers
Kind :
Book Rating : 282/5 ( reviews)

Sentiment Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Sentiment Analysis write by Bing Liu. This book was released on 2020-10-15. Sentiment Analysis available in PDF, EPUB and Kindle. Sentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes. This fascinating problem offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis. This comprehensive introduction to the topic takes a natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs commonly used to express opinions, sentiments, and emotions. The book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. In addition to traditional computational methods, this second edition includes recent deep learning methods to analyze and summarize sentiments and opinions, and also new material on emotion and mood analysis techniques, emotion-enhanced dialogues, and multimodal emotion analysis.

Sentiment Analysis and Opinion Mining

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Author :
Release : 2012
Genre : Computers
Kind :
Book Rating : 849/5 ( reviews)

Sentiment Analysis and Opinion Mining - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Sentiment Analysis and Opinion Mining write by Bing Liu. This book was released on 2012. Sentiment Analysis and Opinion Mining available in PDF, EPUB and Kindle. 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

Text Mining with R

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Release : 2017-06-12
Genre : Computers
Kind :
Book Rating : 628/5 ( reviews)

Text Mining with R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Text Mining with R write by Julia Silge. This book was released on 2017-06-12. Text Mining with R available in PDF, EPUB and Kindle. Chapter 7. Case Study : Comparing Twitter Archives; Getting the Data and Distribution of Tweets; Word Frequencies; Comparing Word Usage; Changes in Word Use; Favorites and Retweets; Summary; Chapter 8. Case Study : Mining NASA Metadata; How Data Is Organized at NASA; Wrangling and Tidying the Data; Some Initial Simple Exploration; Word Co-ocurrences and Correlations; Networks of Description and Title Words; Networks of Keywords; Calculating tf-idf for the Description Fields; What Is tf-idf for the Description Field Words?; Connecting Description Fields to Keywords; Topic Modeling.