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The purpose of this paper is to investigate hazards for minor users while they are exposed to social networks. In particular, it provides the statistical relationship of these hazards with the exposure time as well as the amount of published personal information.

An experiment was conducted that has revealed a huge number of personal information exposed by users of social network applications. Moreover, a significant amount of suspicious activity against minors has been recorded. Experimental data led to the hypothesis that online hazards can be modeled with known statistical distributions. In order to examine this hypothesis, survival analysis techniques, which involve the estimation of certain functions that reflect the relation of a disastrous event with time, were applied.

The results show that the incoming hazards for minor female profiles follow the Logistic distribution, while the corresponding hazards for minor male profiles follow the Normal distribution.

The findings of this work are crucial for developing an effective system for automated grooming recognition in real time by optimizing the detection threshold as a function of time. Thus, the threshold sensitivity can be appropriately adjusted such that lower frequencies of occurrence lead to lower threshold sensitivities, and higher frequencies of occurrence lead to higher threshold sensitivities.