Internet Application Advances in internet applications are increasingly allowing users to perform complex tasks, which are more network centric, omnipresent, knowledge intensive, and computing demanding (Wen-Chung et al, 2010). Today, more than ever before, internet users can use internet applications such as Weka4WS to mine data. According to Talia & Trunfio (2010), Weka4WS is a broadly used open source data mining tool that utilizes the distributed architecture to allow the mining of data in WS-Resource Framework (WSRF) enabled grids. Problems Associated with Text Mining Some of the problems associated with text mining, according to Lee at al (2010), include: word mismatch challenges; difficulties in determining the number of topics; incapacity by some tools to model relations among topics; difficulties in labeling a topic in some applications using words in the topic, and; difficulties in interpreting loading values with probability meaning. How Text Mining has affected the Internet Text mining, also referred to as text analytics, has affected the internet in major ways. In its most basic element, text mining refers to the process of extracting important data and knowledge from unstructured text through a process that employs strong sifting protocols to enable users sieve trivial information from important data (Weiss et al, 2010). Owing to the importance of data in managing customer relationships, forecasting business scenarios, and in making important decisions, organizations across the world are making heavy investments in information and communication technologies in a focused attempt aimed at bringing information closer to where it is mostly needed. The internet happens to be a major carrier of contextual data, and hence it has been influenced in major ways by text mining processes and applications (Feldman & Sanger, 2006). The internet is increasingly been used by people in need of discovering new information. For example, most marketing executives are increasingly using the internet to discover about new and industry-specific trends in fulfilling customer demands. It is important to note that such discoveries require 100% recall; that is, these marketing executives cannot afford to miss any relevant information, thus the need to engage in text mining as opposed to conducting a search on the internet using a standard search engine (Weiss et al, 2010). This orientation underlines how text mining has affected the use of the internet. In equal measure, it can be argued that the internet and the World Wide Web are availing enormous quantities of data easily accessible for analysis and consumption through the process of text mining. Indeed, it is a difficult task to overstate the impact of the internet on the dissemination and sharing of critical information. This observation implies that text mining is to a large extent dependent on the internet in the same vein as the internet has proved valuable to most professional users due to the availability of text mining processes (Weiss et al, 2010). It is common knowledge that the internet contains vast amounts of information, which may prove to be of no germane value in the absence of text mining processes and applications. For example, a financial analyst may be unable to find value in thousands upon thousands of financial-related documents found