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Automatic Categorization of Reviews and Opinions of Internet: E-Shopping Customers

Author

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  • Jan Žižka

    (Mendel University in Brno, Czech Republic)

  • Vadim Rukavitsyn

    (Mendel University in Brno, Czech Republic)

Abstract

E-shopping customers, blog authors, reviewers, and other web contributors can express their opinions of a purchased item, film, book, and so forth. Typically, various opinions are centered around one topic (e.g., a commodity, film, etc.). From the Business Intelligence viewpoint, such entries are very valuable; however, they are difficult to automatically process because they are in a natural language. Human beings can distinguish the various opinions. Because of the very large data volumes, could a machine do the same? The suggested method uses the machine-learning (ML) based approach to this classification problem, demonstrating via real-world data that a machine can learn from examples relatively well. The classification accuracy is better than 70%; it is not perfect because of typical problems associated with processing unstructured textual items in natural languages. The data characteristics and experimental results are shown.

Suggested Citation

  • Jan Žižka & Vadim Rukavitsyn, 2011. "Automatic Categorization of Reviews and Opinions of Internet: E-Shopping Customers," International Journal of Online Marketing (IJOM), IGI Global, vol. 1(2), pages 68-77, April.
    • Handle: RePEc:igg:jom000:v:1:y:2011:i:2:p:68-77
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