Building a Model in Discovering Multivariate Causal Rules for Exploratory Analyses

Causality as a phenomenon still seems to be an old and open issue as the philosophy itself. Discovering such relationships among data, in most of cases results in unsuccessfully effort. Taking in consideration the fact that the research community mostly focuses on the discovery of causal association rules with a single cause factor, but however, sometimes a single variable might not cause any effect, since the problem in most cases is affected by not a single, but by the combination of two or more factors or variables. Anyway, considering the literature located on the web, it is obvious the poor elaboration of causality in cyberstalking, albeit through the history of humanity, stalking was a big issue for the human race. However, it is more prevalent at younger ages. In compliance to this, the empirical approach of cyberstalking has received less attention from worldwide researchers. Consequently, main goal in this manuscript was to perceive and establish the causes that lead to cyberstalking on high school youngsters. Accordingly, a logistic model was built and evaluated by utilizing the confusion matrix. The effort resulted in exogenous model, meaning that beside the factors from our observation, cyberstalking causality is likewise dependent from external factors.