How Data Management Helps the Information Management: Regrouping Data Using Principal Components Analysis

The present study estimates the central factors that influence political behavior. We use data of 1995-1996, of 2006 and of 2010 so as to see how people understand, evaluate and regroup different factors using Principal Components Analysis. The PCA method reveals hidden or latent structures in the data. PCA is used as an exploratory tool in a complex phenomenon such as political behavior so as to get structural components (factors). Instead of using the original variables we use the proper similarity coefficients. So, the matrix of similarity coefficients was analyzed, since it is difficult to check the normality assumption for the original variables. Our sample was constituted by 681 individuals that participated in the interview process. This research is one of the first attempts to depicture different voters’ profiles. From this research exist, today, only some data. Thus, the relationship or the differences among variables cannot be explored. The study presents a historical research that took place in a period when many political and social changes happened, e.g. the change of the main leading figures of the Greek political scene, the deregulation of radio and television as well as the development of internet.