Previous research on detecting risky online behavior has been rather scattered, typically identifying single risks in online samples. To our knowledge, the presented research is the first that presents a process of building models that can efficiently detect the following four online risky behavior: (1) aggression, harassment, hate; (2) mental health; (3) use of alcohol, and drugs; and (4) sexting. Furthermore, the corpora in this research are unique because of the usage of private instant messaging conversations in the Czech language provided by adolescents. The combination of publicly unavailable and unique data with high-quality annotations of specific psychological phenomena allowed us for precise detection using transformer machine learning models that can handle sequential data and involve the context of utterances. The impact of the context length and text augmentation on model efficiency is discussed in detail. The final model provides promising results with an acceptable F1 score. Therefore, we believe that the model could be used in various applications, e.g., parental applications, chatbots, or services provided by Internet providers. Future research could investigate the usage of the model in other languages.

Home users of information and communication technologies are often the target of online attacks. At the same time they tend to lack the knowledge and skills to effectively protect themselves. Families with children are in a particularly difficult position since parents are responsible not only for their own digital safety, but of their children’s too. This study focuses on the sources of digital security information used by parents. The aim of this study was to determine the factors that are associated with parents’ preferences for digital security information. To achieve this aim, we conducted an online survey of 331 Czech parents and examined the patterns of sources used for digital security information using latent class analysis. This analysis identified four groups of parents: (1) those relying predominantly on the internet in general, (2) those using specialised sources (expert websites and professionals), (3) those utilising a wide spectrum of sources, including internet, television, and friends and family, and (4) those who predominantly gain information from their partners, and partially from specialists. The study also shows that the preferences of specific sources are connected to parental mediation practices and both parents’ internet skills.