Sentiment Analysis and Opinion Mining
Sentiment Analysis and Opinion Mining

Sentiment Analysis and Opinion Mining

Liu, Bing

Editorial:
Morgan and Claypool Publishers
ISBN:
978-1-60845-884-4
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 th... Más información
Materias:
Editorial:
Morgan and Claypool Publishers
Encuadernación:
Tapa blanda o Bolsillo
Idioma de publicación :
Inglés
ISBN:
978-1-60845-884-4
EAN:
9781608458844
Dimensiones:
2350 x 1910 mm.
Nº páginas:
180
Fecha publicación :
24-05-2012
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    Sinopsis

    Sinopsis de: "Sentiment Analysis and Opinion 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.

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    Liu, Bing

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