Typology of Cybercrime Victimization in Europe: A Multilevel Latent Class Analysis
Claire Seungeun Lee, Yan Wang
Abstract
The present study reveals hidden patterns of group membership across cybercrime victims in European countries. We used a multilevel latent class analysis of data from the 2019 Eurobarometer, a regionally representative sample of 21,908 individuals from 28 countries, to identify such subgroups and patterns of cybercrime victimization. The findings suggest there are two overarching cybercrime victim profiles in Europe based on individuals’ levels of “online activity” and “cybersecurity guardianship”: the “at-risk class” (19%, higher risk) and the “cautious class” (81%, lower risk). Ten different types of cybercrime victimization were compared, and while individual-level predictors were primarily used to produce different groups of cybercrime victims, our findings suggest that researchers consider both individual- and country-level predictors to understand cybercrime victimization patterns in greater depth.