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 among actors in the system (e.g., providers and users). Some undesirable dependences could be hidden by this layer stacking, implying a reduced transparency for users. Thus, any software is directly dependent of the underlying layers. If one of these layers misbehave, 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 will help to deduce the potential trust a user 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 between actors of the system. SocioPath helps to make evident dependences among participants in the digital world which also introduces dependences at a sociological level. The notions presented in this approach are underneath many fields as 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.