Finer Granularity Clustering for Opinion Mining

The boom of opinion-rich resources such as online review websites, discussion groups, personal blogs and forums on the web has attracted many research efforts on opinion mining. Positive and negative opinions represented in review documents are helpful information for governments to improve their services, for companies to market their products, and for customers to purchase their commodities. In this paper, we introduce a new approach that employs finer granularity clustering for opinions extraction and clustering for the calculation of their sentiment orientation of opinions. The experimental result shows that the approach is qualitatively quite useful when used to analyze the netizens’ opinions to hot topics from some websites.