Mining Message Board Content on the World Wide Web for Organizational Information

Abstract

This chapter proposes a methodology to scan, analyze and classify the content of primarily text-based Web documents to aid an organization in gathering information. The representation and classification of the document is based on the popular vector space model and linear discriminant analysis, respectively. The methodology is developed and demonstrated using real chat room discussions about a publicly traded company collected over a 12-day period. The purpose of this chapter is to develop and demonstrate a methodology used to aid an organization in its environmental scanning efforts, in light of the vast quantities of information available via the Internet.