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Sören Nagel

Publications and source records attributed to Sören Nagel.

3 recordsLinked to original sources

Collective variables for homophily-driven network rewiring dynamics

Stochastic network rewiring processes, in which edges dynamically rewire based on fixed node attributes, are widely used in applications ranging from social dynamics to neuroscience and form an important component of adaptive network modelling. In this paper, we identify low-dimensional collective variables (CVs) that capture the essential macroscopic behavior of such time-evolving networks and enable reduced-order descriptions of their dynamics. To this end, we apply the data-driven transition manifold approach to homophily-driven rewiring models, in which edges preferentially connect nodes with similar attributes. For two representative models, we find that the optimal CV is a consensus measure quantifying the fraction of edges whose incident nodes differ by less than a certain threshold. Building on the learned CV, we construct reduced macroscopic models using a data-driven approach based on sparse regression and through an analytical derivation using graphons. The latter yields a closed-form evolution equation for the consensus measure and analytically validates the identified CV.

physics.soc-ph↗

Co-evolving networks for opinion and social dynamics in agent-based models

The rise of digital social media has strengthened the coevolution of public opinions and social interactions, that shape social structures and collective outcomes in increasingly complex ways. Existing literature often explores this interplay as a one-directional influence, focusing on how opinions determine social ties within adaptive networks. However, this perspective overlooks the intrinsic dynamics driving social interactions, which can significantly influence how opinions form and evolve. In this work, we address this gap, by introducing the co-evolving opinion and social dynamics using stochastic agent-based models. Agents' mobility in a social space is governed by both their social and opinion similarity with others. Similarly, the dynamics of opinion formation is driven by the opinions of agents in their social vicinity. We analyze the underlying social and opinion interaction networks and explore the mechanisms influencing the appearance of emerging phenomena, like echo chambers and opinion consensus. To illustrate the model's potential for real-world analysis, we apply it to General Social Survey data on political identity and public opinion regarding governmental issues. Our findings highlight the model's strength in capturing the coevolution of social connections and individual opinions over time.

physics.soc-ph↗

Capital Inequality Induced Business Cycles

In this letter we present a stochastic dynamic model which can explain economic cycles. We show that the macroscopic description yields a complex dynamical landscape consisting of multiple stable fixed points, each corresponding to a split of the population into a large low and a small high income group. The stochastic fluctuations induce switching between the resulting metastable states, and excitation oscillations just below a deterministic bifurcation. The shocks are caused by the decisions of a few agents who have a disproportionate influence over the macroscopic state of the economy due to the unequal distribution of wealth among the population. The fluctuations have a long-term effect on the growth of economic output and lead to business cycle oscillations exhibiting coherence resonance, where the correlation time is controlled by the population size which is inversely proportional to the noise intensity.

physics.soc-ph↗