A unified framework for net effects in signed social and ecological networks

Abstract

Abstract With improvements in data resolution and quality, researchers can now represent complex systems as signed, weighted, and directed networks. In this article, we introduce a framework for measuring net and indirect effects without simplifying these information-rich networks. It captures both direct and indirect interactions, the effect of the whole network on a node, and conversely, the effect of a node on the entire network, while accommodating the complexity of signed, weighted, and directed links. Our taxonomy unifies and extends existing approaches and measures from network science, computational social science, and ecological networks. We demonstrate its value in ecological systems, where net and indirect effects are critical yet difficult to quantify. Using generalized Lotka–Volterra dynamics, we find a strong correlation between negative net effects and species extinction. We further apply the framework to a real-world social network, where it identifies informative rankings that illuminate influence propagation and power dynamics.