Automatic Opinion Extraction from Web Documents

Automatic extraction of human opinions from Web documents has been receiving increasing interest. An important part of the information-gathering behavior has always been to find out what other people think. With the growing availability and popularity of opinion-rich resources such as online review sites and personal blogs, new opportunities and challenges arise as people can, and do, actively use information technologies to seek out and understand the opinions of others. The sudden eruption of activity in the area of opinion mining, which deals with the computational treatment of opinion and subjectivity in text, has thus occurred at least in part as a direct response to the surge of interest in new systems that deal directly with opinions as a first-class object. In this paper, we demonstrate an opinion mining framework that extracts the opinions and views of the consumers/customers, and analyze them to provide concrete market flow along with proven statistical data. The software uses classification, clustering and lingual knowledge-based opinion mining for providing these features.