标题： 测量有符号生态和社会网络中的净效应 显示英文标题

标题： Measuring net effects in signed ecological and social network

摘要： 随着数据分辨率和质量的提高，研究人员现在可以构建复杂系统的详细表示，作为带符号、加权和有向的网络。 在本文中，我们介绍了一个框架，用于测量净效应和间接效应，而无需简化这些信息丰富的网络。 基于Katz中心性的推广，该框架捕捉了直接和间接相互作用，整个网络对节点及其反向的影响，以及节点对整个网络的影响，同时适应带符号、加权和有向边的复杂性。 为了说明我们的贡献，我们提出了一种分类法，统一了文献中现有的方法和度量。 然后我们将我们的度量应用于生态网络，其中净效应和间接效应仍然是影响共存的关键但难以量化因素。 具体而言，我们在广义Lotka-Volterra动力学中观察到负净效应与物种灭绝之间的强相关性。 此外，我们在一个现实世界的社会网络上测试了我们的框架，它有效地识别了有信息的重要排名，提供了关于影响传播和权力动态的见解。 显示英文摘要

摘要： With improvements in data resolution and quality, researchers can now construct detailed representations of 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. Building on a generalization of Katz centrality, this framework captures both direct and indirect interactions, the effect of the whole network on a node and its reverse, the effect of a node on the whole network, while accommodating the complexity of signed, weighted, and directed edges. To contextualize our contribution, we propose a taxonomy that unifies existing approaches and measures from the literature. We then apply our measure to ecological networks, where net and indirect effects remain critical yet difficult to quantify factors influencing coexistence. Specifically, we observe a strong correlation between negative net effects and species extinction in generalized Lotka-Volterra dynamics. Additionally, we test our framework on a real-world social network, where it effectively identifies informative importance rankings, providing insights into influence propagation and power dynamics.