AUTHOR=Casiraghi Giona , Schweitzer Frank TITLE=Improving the Robustness of Online Social Networks: A Simulation Approach of Network Interventions JOURNAL=Frontiers in Robotics and AI VOLUME=7 YEAR=2020 URL=https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2020.00057 DOI=10.3389/frobt.2020.00057 ISSN=2296-9144 ABSTRACT=

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.