A Comparison of Sentiment Analysis Techniques: Polarizing Movie Blogs

  • Michelle Annett
  • Grzegorz Kondrak
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5032)

Abstract

With the ever-growing popularity of online media such as blogs and social networking sites, the Internet is a valuable source of information for product and service reviews. Attempting to classify a subset of these documents using polarity metrics can be a daunting task. After a survey of previous research on sentiment polarity, we propose a novel approach based on Support Vector Machines. We compare our method to previously proposed lexical-based and machine learning (ML) approaches by applying it to a publicly available set of movie reviews. Our algorithm will be integrated within a blog visualization tool.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Michelle Annett
    • 1
  • Grzegorz Kondrak
    • 1
  1. 1.Department of Computing ScienceUniversity of Alberta 

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