• Erik Cambria
  • Amir Hussain
Part of the SpringerBriefs in Cognitive Computation book series (BRIEFSCC, volume 2)


In a world in which millions of people express their opinions about commercial products in blogs, wikis, forums, chats, and social networks, the distillation of knowledge from this huge amount of unstructured information can be a key factor for marketers who want to create an image or identity in the minds of their customers for their product, brand, or organisation. The automatic analysis of online opinions, however, involves a deep understanding of natural language text by machines, from which we are still very far. Online information retrieval, in fact, is still mainly based on algorithms relying on the textual representation of web pages. Such algorithms are very good at retrieving texts, splitting them into parts, checking the spelling, and counting their words. But when it comes to interpreting sentences and extracting useful information for users, their capabilities are still very limited.


Opinion Mining Sentiment Analysis Affective Computing Affective Information Natural Language Text 
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

© The Author(s) 2012

Authors and Affiliations

  1. 1.Media LaboratoryMassachusetts Institute of TechnologyCambridgeUSA
  2. 2.Department of Computing ScienceUniversity of StirlingStirlingUK

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