Abstract
We introduce a dynamic model for network participation and resource-sharing problems grounded in non-cooperative game theory. Within a social network, individuals must decide whether to join cooperative activities or share resources based on anticipated benefits versus incurred costs. We cast these problems as non-cooperative games and comprehensively characterize the Nash equilibria in these settings. Furthermore, we introduce Log-Linear Learning (LLL) as a potential decision strategy for the participants and analyze the long-term dynamics of this approach within the framework. We perform extensive simulations on random networks to empirically validate our research findings. These simulations provide compelling evidence that within our proposed framework, user engagement in network participation and sharing dilemmas closely aligns with the well-established concepts of k-\mathbf{core} and (r,s)-\mathbf{core} within network structures.