An Effective Multidimensional Model for Analyzing Social Web Big Data – Testing in simple Web 2.0 Applications of Internet Politics

Abstract

Web 2.0 applications have provided researchers with vast quantities of Big Data, opening up new horizons for developing innovative analysis techniques that are applicable in multiple cognitive fields. Politics is definitely among them and is currently in a dynamically evolving range of these applications. Although modern Social Networking Platforms dominate the digital political landscape by supporting impressive volumes of political Big Data, political trends could nevertheless be traced in the pioneering network of one of the first participatory web applications: the blogs. The blogs and their social network, the so-called blogosphere, featured most of the advanced characteristics of contemporary Social Media Platforms, in a more simplistic form. After 15 years of digital existence, they maintained a noticeable presence in the Social Web while they have additionally undertaken the role of gateways to the multifaceted realm of Social Media Networks. Since their introduction, they have been providing digital citizens with a user-friendly tool to post political content, mutually interact, shape the political agenda and horizontally influence the public opinion as well as vertically affect the administrative decision centers. Therefore, they can be used as a reach Big Data fields suitable for testing multidimensional modeling methods towards mapping political trends, which could be upgraded accordingly for use in more complicated Social Media Applications. In this paper, a qualitative as well as quantitative method for analyzing the political blogosphere is introduced, consisting of three components. It focuses on the formation of blog communities, based on their hyperlink interconnectivity, the blogs’ influence and their users’ generated content. By applying a Multidimensional Scaling and Cluster Analysis, clusters were located, which correspond to the afore mentioned communities. These clusters, were found to be somehow related to the degree they may potentially influence their readers. Findings showed that high influence does not always involve high rates of hyperlinking. Eventually, by applying Content Analysis to the content of the blogs forming the clusters, the qualitative characteristics and the general topics of the political discussion were identified, regarding the specific survey period. Findings suggested that the qualitative characteristics of the political blogs are significantly related to the cluster they belong to, according to their hyperlinking. In the case study presented, the method proved to be able to investigate both the political qualitative and quantitative blogosphere characteristics. By applying it in the Greek political blogosphere, it proved to be able to thoroughly investigate the political debate that takes place on a portion of the social web, its characteristics and the influence it potentially has on public opinion.