Survey Analyses of The Specific Impacting Factors in Devising a Machine Learning Prediction model for The General Election Process in Kosovo

Abstract

The focus of the research study was analyses of impacting factors and later to incorporate those insights into variables to be measured for devising a machine learning predictive model for prognosis and prediction of the general election turnout in Kosovo. We have developed a novel method for recognizing the main impacting factors in elections. Our method shows that finding out whether different ways of collecting different data of election voters can lead to much better prediction and understanding of the election process. In order to do that we needed to analyze the specific impacting factors in the election process in Kosovo are investigated during the study. The data has derived from an originally collected survey dataset that contains the impacting factors previously identified and assessed regarding the general parliamentary elections in Kosovo  has been realized. Insights and recommendation has been discussed and argumented.