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Web Data Mining pp 459–526Cite as

Opinion Mining and Sentiment Analysis

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Part of the book series: Data-Centric Systems and Applications ((DCSA))

Abstract

In Chap. 9, we studied the extraction of structured data from Web pages. The Web also contains a huge amount of information in unstructured texts. Analyzing these texts is of great importance as well and perhaps even more important than extracting structured data because of the sheer volume of valuable information of almost any imaginable type contained in text. In this chapter, we only focus on mining opinions which indicate positive or negative sentiments. The task is technically challenging and practically very useful. For example, businesses always want to find public or consumer opinions on their products and services. Potential customers also want to know the opinions of existing users before they use a service or purchase a product.

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  1. Department of Computer Science, University of Illinois, Chicago, 851 S. Morgan St., Chicago, IL, 60607-7053, USA

    Bing Liu

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Liu, B. (2011). Opinion Mining and Sentiment Analysis. In: Web Data Mining. Data-Centric Systems and Applications. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19460-3_11

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  • DOI: https://doi.org/10.1007/978-3-642-19460-3_11

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