Data Breach in Social Networks Using Machine Learning

Abstract

There is a huge concern over privacy of data and security breaches in the upcoming area pertinent to digital services. There is a phenomenal increase in social media sites so as the increase in the volume of data. Therefore, from the linguistic perspective, to understand and analyze the data has become a complex procedure. In this paper, the investigation is done on the information characteristics which are attributed to data breach messages, first we create a questionnaire to know the basic information about the purpose of using social media applications by various users and their awareness regarding the data breach through these applications and secondly, we tried to find out some meaningful insight out of the data collected to reach to some logical conclusion. A quite different pattern is followed by breach information diffusion in contrast to the conventional news channels where the related posts are subjected to wide attention on social media. The widely shared messages among the tech-savvy groups and the personnel involved in the studies related to security are the key factors. Researchers can mine down the grounded insights to the research questions by analyzing the messages in the field of linguistic and visual perspective over social media. This primary research has been done to analyze people’s perception towards digitalization and how the risk of data breach has affected them in using some of the most widely used social media application. © 2022, Springer Nature Switzerland AG.