Author: cxdig

Anna Guerrero | How to Model Science as a Complex System

Tracing the historical dynamics of science can reveal how scientific knowledge emerges and evolves over time. Because scientific knowledge is embedded in increasingly complex systems, comprising shifting relationships among people, the organisms and matter they study, technology, data, publications, and the concepts they utilize, scholars are looking beyond traditional historiographical methods towards quantitative and computational tools. Big data, network analysis, and machine learning enhance the scale and speed of analysis, but these methods often ignore or erase the critical roles that context (like time period, geography, and discipline) and different types of data (like image and audio data) play in the development of new knowledge. In this talk, I present context- and data-sensitive computational methods that extend efforts to model the evolution of science as a complex system. These methods reveal when new knowledge emerges and how the features of old scientific information constrain features of new scientific knowledge.

Read the full article at: www.mivideo.it.umich.edu

Exploring Cultural Evolution Through Modular Dynamics in Temporal Hashtag Networks

Yasuhiro Hashimoto, Hiroki Sato, and Takashi Ikegami

Entropy 2026, 28(4), 398

Social media platforms offer unprecedented opportunities to study cultural evolution by analyzing digital traces. This study presents a methodological framework for analyzing the temporal dynamics of cultural modules in hashtag co-occurrence networks. We address the inherent challenges of analyzing dense, skewed, and highly variable cultural networks by introducing a perturbation ensemble clustering approach that distinguishes stable from unstable structural elements. By applying the Leiden algorithm to a perturbed ensemble of hashtag networks, we identify robust core modules and their stable periphery, and distinguish them from floating elements with unstable associations. Analysis of four years of data from a major photo-sharing platform reveals complex patterns in the evolution of cultural modules, including both stable associations and dynamic reorganizations. Our findings demonstrate how ensemble clustering techniques can effectively capture the interplay between stability and change in evolving cultural systems.

Read the full article at: www.mdpi.com

Breaking the code: Multi-level learning in the Eurovision Song Contest

Luis A. Nunes Amaral; Arthur Capozzi; Dirk Helbing
R Soc Open Sci. (2026) 13 (4): 251727 .

Organizations learn from market, political and societal responses to their actions. While in some cases both the actions and responses take place in an open manner, in many others, some aspects may be hidden from external observers. The Eurovision Song Contest offers a mostly open-data case in which to study organizational level learning at the levels of organizers and participants. We present here evidence for changes in the rules of the Contest in response to undesired outcomes such as runaway winners. We also find strong evidence of participant learning in the characteristics of competing songs over the 70 years of the Contest. English has been adopted as the lingua franca of the competing songs and pop has become the standard genre. The number of words of lyrics has also grown in response to this collective learning. Remarkably, we find evidence that France, Italy, Portugal and Spain have chosen to ignore the ‘lesson’ that English lyrics increase winning probability, consistent with utility functions that award greater value to featuring national culture than to winning the Contest. These countries—but not Germany—appear to be less susceptible to Anglo-Saxon cultural influence than their peers, a resistance that may extend beyond cultural matters.

Read the full article at: royalsocietypublishing.org

Probabilistic punishment proportional to the payoff difference solves the problem of antisocial punishment

Tetsushi Ohdaira

Chaos, Solitons & Fractals
Volume 208, Part 4, July 2026, 118382

This study modifies the model in the previous studies and considers three types of inter-individual relationships: regular, random, and scale-free ring lattices. Furthermore, we introduce defectors, who do not contribute to the public goods; cooperators, who contribute to the public goods; and loners, who do not participate in the public goods framework. We assume that each of these three types of individuals punishes other individuals with a probability proportional to the difference between their own payoff and their opponent’s average payoff including them. Using this modified pool punishment model, this study shows the following. Firstly, the damage to the average payoff due to excessive punishment is kept significantly low. Secondly, antisocial punishment is not evolutionarily advantageous, and cooperators always become advantageous. Finally, the final average payoff is always higher than that of pool punishment in existing studies and roughly comparable to that of peer punishment in existing studies. The results of this study provide new insights that the claim of the existing study is not always correct; that is, even if antisocial punishment is possible, it does not have an evolutionary advantage, and cooperators always become advantageous, which in turn solves the problem of antisocial punishment. This study is being conducted as part of efforts to improve specialized education at Kanagawa Institute of Technology.

Read the full article at: www.sciencedirect.com

Tipping Out of Trouble: How Societies Transformed and How We Can Do So Again, by Marten Scheffer

What kind of trouble lies ahead? How can we successfully transition towards a sustainable future? Drawing on a remarkably broad range of insights from complex systems and the functioning of the brain to the history of civilizations and the workings of modern societies, the distinguished scientist Marten Scheffer addresses these key questions of our times. He looks to the past to show how societies have tipped out of trouble before, the mechanisms that drive social transformations and the invisible hands holding us back. He traces how long-standing practices such as the slave trade and foot-binding were suddenly abandoned and how entire civilizations have collapsed to make way for something new. Could we be heading for a similarly dramatic change? Marten Scheffer argues that a dark future is plausible but not yet inevitable and he provides us instead with a hopeful roadmap to steer ourselves away from collapse-and toward renewal.

More at: www.cambridge.org