## 3 Results
### Privacy Management
Despite the fact that participants have rated really highly their belief in their right to control their privacy, findings indicate that they do not rate that high their practice of considering social networks privacy policy (M = 2.9), while they declare of achieving a medium level of the appropriateness of their uploaded information related to different audiences (M = 3). Furthermore, they also rate low enough their ability to have control on the audiences that have access to their information (M = 2.18). These indicate the necessity for more effective privacy solutions within SNs that they will provide users with more control on the handling of their information. The participants' responses for privacy control within SNs are fully presented in the following Figure 4.  
Figure 4: Privacy Control. Figure 3: Self-disclosure. Previous literature has shown that users, due to gaining benefits from their social networks, do not weight considerably enough the privacy risks posed by information-sharing activities [53], and therefore their privacy awareness should be enhanced. Findings show that participants declare that they have a medium level of privacy awareness, especially as far as the privacy solutions that law and social networks employ (M = 3.02). However, it is encouraging that participants recognize and rate much higher that their personal information has value for the providers of social networks services (M = 3.86). This information sharing among users can be a cause of potential risks for each one separately. Personal information disclosures of a user for other users, regardless other users' approval, are common practices within SNS [62]. Findings support this previous knowledge, since participants rate highly enough (M = 3.69) only their own behaviour of asking approval, before disclosing information of their group members. As far as their group members concern, the rating is much lower. The participants' responses regarding the collaborative privacy management within SNs are presented in detail as follows in Figure 5.  
Previous literature regarding Privacy Calculus [63] shows that users estimate the information disclosure costs and benefits in social networks, indicating that the benefits are constantly irresistible for most of the users. However, our findings highlight that participants evaluate lower the services deriving from their participation in social networks than their privacy concerns and the risks posed due to it. Our results indicate that, in order to support the design of self-adaptive privacy protection schemes within SNs, users' privacy social and technological context should be considered. SNs cause plenty of privacy concerns for users, while it is highlighted that they do not fulfill their privacy needs or provide them with the adequate trust. Aiming to support this design of self-adaptive privacy safeguard within SNs and the identification of specific privacy related requirements, it is necessary to provide specific constructs that reflect users, SNs and self-adaptive privacy protection schemes parameters in a pilot taxonomic way, as follows. The users within SNs:  
1. Heterogeneous: The users are determined by several social identities, which reflect not only their individual social norms that they are dynamic, but also their reciprocal arrangements with the groups in which they belong within SNs. 2. Social Interrelated: The users provide access and disclose their personal information in order to gain plenty of symbolic benefits and resources, deriving from their online social networks. 3. Privacy oriented: The users value the significance of privacy rights on a high level and they raise plenty of privacy concerns when utilizing SNs, while they are  
Figure 5: Collaborative Privacy Management. characterized by a minimum degree of trust regarding the use of their personal information. * Collaborative: The users co-manage their personal information with other users and they disclose information concerning other users, without, in many cases, having their approval. The SNs environment: 1.