Ubiquitous social networking focuses on developing possible advantageous relationships such as friendships, partnerships and business relations in the physical world, by uncovering hidden connections that people share with others nearby. The foundation of these services is based on disclosure of personal information, which can provoke numerous accidental invasions of privacy. This dissertation contributes by addressing two problems, related to support of privacy-aware social networking in ubiquitous computing environments that focus on maximizing potential networking benefits while preserving users' privacy. Firstly, it updates the current privacy guidelines of ubiquitous computing by proposing four drawbacks to be avoided when designing for privacy in ubiquitous social networking environments. Secondly, this dissertation identifies and investigates the determinants that might influence the variation of human data sensitivity under different circumstances, for ensuring accuracy of selective disclosure of personal data. By taking into account the proposed design guidelines and identified influential factors, this dissertation seeks to provide relevant insights into data disclosure for contributing to development of privacy-aware social networking in ubiquitous computing environments.