  Online social networks (OSN) are prime examples of socio-technical systems in
which individuals interact via a technical platform. OSN are very volatile
because users enter and exit and frequently change their interactions. This
makes the robustness of such systems difficult to measure and to control. To
quantify robustness, we propose a coreness value obtained from the directed
interaction network. We study the emergence of large drop-out cascades of users
leaving the OSN by means of an agent-based model. For agents, we define a
utility function that depends on their relative reputation and their costs for
interactions. The decision of agents to leave the OSN depends on this utility.
Our aim is to prevent drop-out cascades by influencing specific agents with low
utility. We identify strategies to control agents in the core and the periphery
of the OSN such that drop-out cascades are significantly reduced, and the
robustness of the OSN is increased.
