Self-disclosure in Social Media: An Opportunity for Self-Adaptive Systems

Abstract

Users of Social Network Sites (SNSs) spend considerable amounts of hours per day exchanging (consuming or sharing) informa- tion and using services provided by such platforms. However, nothing comes for free. SNSs survive at the expense of the information that users’ upload to their profiles, and the knowledge derived from their on-line be- havior. Discovering hidden knowledge in social networks is a centerpiece in many personalized on-line services and ad-targeting techniques, and helps to make a SNS profitable. However, users seem not to be aware of this common practice and keep sharing content compulsively. Never- theless, self-disclosure and over-exposition can have severe consequences and can put users’ integrity into risk. In order to develop better infor- mation control and awareness systems, we believe that it is important to take into account the users’ on-line habits and behavior. In this work we introduce an initial assessment of the different factors that contribute to self-disclosure in Social Media, and discuss the elements that a self- adaptive solution should consider to address this issue.

Publication
Joint Proceedings of the 22nd International Conference on Requirements Engineering: Foundation for Software Quality (REFSQ), vol. 1564

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