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Opinion Mining and Sentiment Analysis

  • Bing LiuEmail author
Chapter
Part of the Data-Centric Systems and Applications book series (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.

Keywords

Natural Language Processing Opinion Mining Conditional Random Field Negative Opinion Computational Linguistics 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of Illinois, ChicagoChicagoUSA

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