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

Jan Žižka and Vadim Rukavitsyn
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Jan Žižka: Mendel University in Brno, Czech Republic
Vadim Rukavitsyn: Mendel University in Brno, Czech Republic

International Journal of Online Marketing (IJOM), 2011, vol. 1, issue 2, 68-77

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.

Date: 2011
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International Journal of Online Marketing (IJOM) is currently edited by Hatem El-Gohary

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