## 4 Discussion  
Users' privacy protection within SNs is an ongoing process, depending on social, legal, and technical aspects [64]. However, their inadequate bridging arises difficulties for an effective privacy protection solution [65], compliant to GDPR principles and rules as well. Towards this, several self-adaptive privacy solutions under the differential privacy scheme [66] or under the context-adaptive privacy scheme [67; 68], have been introduced. However, they were subsequent to many limitations, since they did not identify in depth users' social landscape and outlet, failing therefore to correlate them with the appropriate privacy technical solutions [69]. Thus, as we, in detailed, have discussed in a previous work, since self-adaptive privacy focuses on users' integrated context, both social and technical, a group of criteria should be satisfied for its optimal design. Among these, the thoroughly investigation of users' social norms is a focal one and the first step in order for the self-privacy related requirements to be elicited. The determining of users' social attributes will provide developers with further knowledge so as to, not only to include social requirements at their design, but also to build the appropriate technical privacy affordances. After all, previous research for self-adaptive privacy has shown that not enough attention is paid on eliciting requirements from the users' perspective, in order for introducing flexibility in the self-adaptive systems behavior at an early phase of requirements engineering [70], a prerequisite for the implementation of PhD principle. In this regard, our survey highlights the social attributes of a targeted research population within the academic community of a Greek University, this of the academic and administrative staff of the University of the Aegean. It should be noted that, although the utilization and the impact of social networks is growing among the populations of the academic educational settings [71], as far as the privacy issues concern in particular, most of previous research focus on students [52] and not on the adults. Under this, the findings of our survey indicate the social landscape of adults SNs users, which is considerable different from this one of the young adults. Our sample, at the majority, has been indicated to be over the 30 years old, highly educated, with many years of professional experience, while keeping in mind Greece's financial situation, it has a descent monthly income. These entire social attributes, examined separately by previous research, have been shown to influence users' privacy perceptions and behaviors [72; 73], leading them to grow their privacy concerns and making them to follow strict enough privacy management strategies when using SNs. Our findings, while supporting previous evidence regarding privacy concerns and self-disclosure practices, indicate that these attributes do not have the same effect as far as the privacy control concerns, showing a low control level. Despite of the high cultural and financial capital of the participants, privacy control remains an issue of great importance for users and therefore an appropriate self-adaptive privacy scheme should provide users with the control level over the information they want to reveal, as it was argued by [74]. Furthermore, participants in our survey, declare to belong to several social groups within SNs, with most dominant the Friends and Family Groups. This indicates that they belong to more than one social categories, which are significant parts of individuals' self-concept. This categorization enables them to distinguish their personal boundaries and these of their memberships. Thus, participants several social categories create concentrations regarding their \"self-interestedness, self-reliance, self-realization and self-determination\", as it is shown from their low or medium rates regarding the positive impact, the importance, and the support that they receive from these groups in SNs.