Application of Data Mining Clustering for Patterns Analysis of Cyberbullying Surveys

Abstract

In latest years, harassment or abuse through mobile devices and the Internet has been on the rise. This issue, better known as cyberbullying, is crueler and more dangerous than the traditional ways of bullying, largely due to the anonymity on social media or the Internet possibly generating consequences across the person’s lifetime. Therefore, different approaches have been developed in the search of alerting, informing, and preventing about cyberbullying situations such as the creation of regulations, issuing laws, or promoting technological approaches. This paper aims to find relevant patterns by applying clustering techniques, and to accomplish this goal, the survey titled the scale of victimization among adolescents through mobile phones and Internet (CYBVIC) has been used allowing to measure behaviors of harassment, aggression and social exclusion. The results obtained by the clustering can be used to combat this social problem, due to this analysis highlights the seven most important questions and the hidden patterns among the filled responses.