Distributed systems are getting more and more numerous, complex and used in a wide variety of applications. New solutions and new architectures arise (e.g., clouds) that support new functionalities (e.g., social networks) and pile up several software layers. This evolution implies new non negligible dependences increasing in the number of actors involved in the system (e.g., providers and users). Some undesirable dependences could be hidden by this layer stacking, implying a reduced transparency for users and a misunderstanding of her actual autonomy. Given that any software is directly dependent of the underlying layers, if any of these layers misbehaves, the given software may be unable to provide promised services. We argue that users should be aware of the potential risks resulting from their dependences. To be able to deduce those dependences, one should know the way the system works (architecture, involved resources, providers, participants, etc.). This would help to deduce the potential trust a user could or should have toward the system. We consider this of utmost importance, as professional efficiency and personal privacy could be compromised if untrusted actors control the access to resources. This work proposes SOCIOPATH, a generic meta-model that allows to expose hidden or implied relationships among participants in the digital world, which also introduce dependences at the social level. The notions presented in this approach are basics of many fields, like security, privacy, trust, sociology, economy and so forth. SOCIOPATH can be used in the evaluation process of a system as well as in its upstream design.