Addressing self-disclosure in social media: An instructional awareness approach

Abstract

Nowadays the information flowing across the different Social Network Sites (SNSs) like Facebook is highly diverse and rich in its content. It is precisely the diversity of the users' contributions to SNSs that makes these platforms attractive and interesting to engage with. Nevertheless, there is a high amount of private and sensitive information being disclosed permanently by these users in order to take full advantage of the services offered by such sites. Current privacy-protection approaches (like the one provided by Facebook) allow users to restrict the audience of their contributions and hide particular pieces of information; however, they are still far from being widely adopted and put proactively into practice. For this reason, we propose to analyze and address different aspects of online self-disclosure in Social Media from a pedagogical and self-adaptive perspective. In this work we introduce the architecture of an Instructional Awareness System (IAS) based on the MAPE-K blueprint for autonomic systems, and provide a definition of its feedback mechanism using principles of Constraint-Based Modeling (CBM).