Sentiment Analysis and Opinion Mining

Name: Sentiment Analysis and Opinion Mining
Brand: Morgan and Claypool Publishers
SKU: 6047167118
Price: 1705 RUB
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Артикул Маркета

6047167118

ISBN

9781608458844

Обложка

мягкий

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офсетная

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Москва

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Москва

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Т8 Издательские Технологии

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Описание

Печатная книга «Sentiment Analysis and Opinion Mining» в мягкой обложке, язык - английский. В книге 180 страниц, она напечатана на белой офсетной бумаге плотностью 80 г/м². Формат издания — 191x235 мм. Все книги аккуратно упаковываем в прочный трехслойный сейф-пакет.
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.