Relating size and functionality in human social networks through complexity

Quasi-critical dynamics in large-scale social systems regulated by sudden events

How do heterogeneous individual behaviors arise in response to sudden events and how do they shape large-scale social dynamics? Based on a five-year naturalistic observation of individual purchasing behaviors, we extract the long-term consumption dynamics of diverse commodities from approximately 2.2 million purchase orders. We subdivide the consumption dynamics into trend, seasonal, and random components and analyze them using a renormalization group. We discover that the coronavirus pandemic, a sudden event acting on the social system, regulates the scaling and criticality of consumption dynamics. On a large time scale, the long-term dynamics of the system, regardless of arising from trend, seasonal, or random individual behaviors, is pushed toward a quasi-critical region between independent (i.e., the consumption behaviors of different commodities are irrelevant) and correlated (i.e., the consumption behaviors of different commodities are interrelated) phases as the pandemic erupts. On a small time scale, short-term consumption dynamics exhibits more diverse responses to the pandemic. While the trend and random behaviors of individuals are driven to quasi-criticality and exhibit scale-invariance as the pandemic breaks out, seasonal behaviors are more robust against regulations. Overall, these discoveries provide insights into how quasi-critical macroscopic dynamics emerges in heterogeneous social systems to enhance system reactivity to sudden events while there may exist specific system components maintaining robustness as a reflection of system stability.

Complexity synchronization in living matter: a mini review

Fractal time series have been argued to be ubiquitous in human physiology and some of the implications of that ubiquity are quite remarkable. One consequence of the omnipresent fractality is complexity synchronization (CS) observed in the interactions among simultaneously recorded physiologic time series discussed herein. This new kind of synchronization has been revealed in the interaction triad of organ-networks (ONs) consisting of the mutually interacting time series generated by the brain (electroencephalograms, EEGs), heart (electrocardiograms, ECGs), and lungs (Respiration). The scaled time series from each member of the triad look nothing like one another and yet they bear a deeply recorded synchronization invisible to the naked eye. The theory of scaling statistics is used to explain the source of the CS observed in the information exchange among these multifractal time series. The multifractal dimension (MFD) of each time series is a measure of the time-dependent complexity of that time series, and it is the matching of the MFD time series that provides the synchronization referred to as CS. The CS is one manifestation of the hypothesis given by a "Law of Multifractal Dimension Synchronization" (LMFDS) which is supported by data. Therefore, the review aspects of this paper are chosen to make the extended range of the LMFDS hypothesis sufficiently reasonable to warrant further empirical testing.

Unveiling the Impact of Communication Network on Engineering Project Team Performance: The Interplay of Centralization and Tie Strength

Purpose

Recent research has focused on the impact of communication networks on the performance of construction project teams, attempting empirical exploration from various social network analysis perspectives. However, there is still a significant gap in understanding the variations in performance and the mechanisms for teams using different communication networks. Drawing from organizational learning theory and social network theory, this study, based on the Input-Mediator-Output (IMO) model, explores the effects of the interaction between centralization and tie strength in communication networks on team performance, as well as the mediating mechanisms of knowledge sharing behavior and team resilience performance in engineering project teams.

Methods

Drawing on classic group communication experiment, we design an online communication and collaboration platform to simulate the execution of a construction engineering project. Finally, data was collected through the communication experiment with 720 participants, and hypotheses were tested using ANOVA and PROCESS.

Results

The results indicate that under conditions of weak tie strength, centralized communication networks yield higher performance. Conversely, under conditions of strong tie strength, decentralized communication networks demonstrate superior performance. Furthermore, this study also verifies the mediating role of knowledge sharing behavior and team resilience performance when tie strength is strong.

Conclusion

This study focuses on engineering project team, exploring the evolutionary development of knowledge sharing behavior and team resilience performance from the perspective of the interaction of communication network structural characteristics, as well as the paths to enhancing team performance. Our research results highlight the interactive effects of structural indicators and relational indicators of communication networks, revealing the mechanism by which the structure of communication networks impacts team performance. Additionally, from the perspectives of forming and timely adjusting team communication models, and motivating and supporting employee communication behavior, our study provides practical insights for project managers and relevant administrators.

Four errors and a fallacy: pitfalls for the unwary in comparative brain analyses

Comparative analyses are the backbone of evolutionary analysis. However, their record in producing a consensus has not always been good. This is especially true of attempts to understand the factors responsible for the evolution of large brains, which have been embroiled in an increasingly polarised debate over the past three decades. We argue that most of these disputes arise from a number of conceptual errors and associated logical fallacies that are the result of a failure to adopt a biological systems-based approach to hypothesis-testing. We identify four principal classes of error: a failure to heed Tinbergen's Four Questions when testing biological hypotheses, misapplying Dobzhansky's Dictum when testing hypotheses of evolutionary adaptation, poorly chosen behavioural proxies for underlying hypotheses, and the use of inappropriate statistical methods. In the interests of progress, we urge a more careful and considered approach to comparative analyses, and the adoption of a broader, rather than a narrower, taxonomic perspective.

Toward reframing brain-social dynamics: current assumptions and future challenges

Evolutionary analyses suggest that the human social brain and sociality appeared together. The two fundamental tools that accelerated the concurrent emergence of the social brain and sociality include learning and plasticity. The prevailing core idea is that the primate brain and the cortex in particular became reorganised over the course of evolution to facilitate dynamic adaptation to ongoing changes in physical and social environments. Encouraged by computational or survival demands or even by instinctual drives for living in social groups, the brain eventually learned how to learn from social experience via its massive plastic capacity. A fundamental framework for modeling these orchestrated dynamic responses is that social plasticity relies upon neuroplasticity. In the present article, we first provide a glimpse into the concepts of plasticity, experience, with emphasis on social experience. We then acknowledge and integrate the current theoretical concepts to highlight five key intertwined assumptions within social neuroscience that underlie empirical approaches for explaining the brain-social dynamics. We suggest that this epistemological view provides key insights into the ontology of current conceptual frameworks driving future research to successfully deal with new challenges and possible caveats in favour of the formulation of novel assumptions. In the light of contemporary societal challenges, such as global pandemics, natural disasters, violent conflict, and other human tragedies, discovering the mechanisms of social brain plasticity will provide new approaches to support adaptive brain plasticity and social resilience.

Why did doctrinal religions first appear in the Northern Subtropical Zone?

Doctrinal religions that involve recognised gods, more formal theologies, moral codes, dedicated religious spaces and professional priesthoods emerged in two phases during the Neolithic. Almost all of these appeared in a narrow latitudinal band (the northern Subtropical Zone). I suggest that these developments were the result of a need to facilitate community bonding in response to scalar stresses that developed as community sizes increased dramatically beyond those typical of hunter-gatherer societies. Conditions for population growth (as indexed by rainfall patterns and the difference between pathogen load and the length of the growing season) were uniquely optimised in this zone, creating an environment of ecological release in which populations could grow unusually rapidly. The relationship between latitude, religion and language in contemporary societies suggests that the peculiar characteristics of the northern (but not the southern) Subtropical Zone were especially favourable for the evolution of large scale religions as a way of enforcing community cohesion.

Beyond collective intelligence: Collective adaptation

We develop a conceptual framework for studying collective adaptation in complex socio-cognitive systems, driven by dynamic interactions of social integration strategies, social environments and problem structures. Going beyond searching for 'intelligent' collectives, we integrate research from different disciplines and outline modelling approaches that can be used to begin answering questions such as why collectives sometimes fail to reach seemingly obvious solutions, how they change their strategies and network structures in response to different problems and how we can anticipate and perhaps change future harmful societal trajectories. We discuss the importance of considering path dependence, lack of optimization and collective myopia to understand the sometimes counterintuitive outcomes of collective adaptation. We call for a transdisciplinary, quantitative and societally useful social science that can help us to understand our rapidly changing and ever more complex societies, avoid collective disasters and reach the full potential of our ability to organize in adaptive collectives.

Managing the stresses of group-living in the transition to village life

Group living is stressful for all mammals, and these stresses limit the size of their social groups. Humans live in very large groups by mammal standards, so how have they solved this problem? I use homicide rates as an index of within-community stress for humans living in small-scale ethnographic societies, and show that the frequency of homicide increases linearly with living-group size in hunter-gatherers. This is not, however, the case for cultivators living in permanent settlements, where there appears to be a 'glass ceiling' below which homicide rates oscillate. This glass ceiling correlates with the adoption of social institutions that allow tensions to be managed. The results suggest (a) that the transition to a settled lifestyle in the Neolithic may have been more challenging than is usually assumed and (b) that the increases in settlement size that followed the first villages necessitated the introduction of a series of social institutions designed to manage within-community discord.

The scaling of social interactions across animal species

Social animals self-organise to create groups to increase protection against predators and productivity. One-to-one interactions are the building blocks of these emergent social structures and may correspond to friendship, grooming, communication, among other social relations. These structures should be robust to failures and provide efficient communication to compensate the costs of forming and maintaining the social contacts but the specific purpose of each social interaction regulates the evolution of the respective social networks. We collate 611 animal social networks and show that the number of social contacts E scales with group size N as a super-linear power-law [Formula: see text] for various species of animals, including humans, other mammals and non-mammals. We identify that the power-law exponent [Formula: see text] varies according to the social function of the interactions as [Formula: see text], with [Formula: see text]. By fitting a multi-layer model to our data, we observe that the cost to cross social groups also varies according to social function. Relatively low costs are observed for physical contact, grooming and group membership which lead to small groups with high and constant social clustering. Offline friendship has similar patterns while online friendship shows weak social structures. The intermediate case of spatial proximity (with [Formula: see text] and clustering dependency on network size quantitatively similar to friendship) suggests that proximity interactions may be as relevant for the spread of infectious diseases as for social processes like friendship.

Social network architecture and the tempo of cumulative cultural evolution

The ability to build upon previous knowledge-cumulative cultural evolution-is a hallmark of human societies. While cumulative cultural evolution depends on the interaction between social systems, cognition and the environment, there is increasing evidence that cumulative cultural evolution is facilitated by larger and more structured societies. However, such effects may be interlinked with patterns of social wiring, thus the relative importance of social network architecture as an additional factor shaping cumulative cultural evolution remains unclear. By simulating innovation and diffusion of cultural traits in populations with stereotyped social structures, we disentangle the relative contributions of network architecture from those of population size and connectivity. We demonstrate that while more structured networks, such as those found in multilevel societies, can promote the recombination of cultural traits into high-value products, they also hinder spread and make products more likely to go extinct. We find that transmission mechanisms are therefore critical in determining the outcomes of cumulative cultural evolution. Our results highlight the complex interaction between population size, structure and transmission mechanisms, with important implications for future research.

Sir Isaac Newton Stranger in a Strange Land

The theme of this essay is that the time of dominance of Newton's world view in science is drawing to a close. The harbinger of its demise was the work of Poincaré on the three-body problem and its culmination into what is now called chaos theory. The signature of chaos is the sensitive dependence on initial conditions resulting in the unpredictability of single particle trajectories. Classical determinism has become increasingly rare with the advent of chaos, being replaced by erratic stochastic processes. However, even the probability calculus could not withstand the non-Newtonian assault from the social and life sciences. The ordinary partial differential equations that traditionally determined the evolution of probability density functions (PDFs) in phase space are replaced with their fractional counterparts. Allometry relation is proven to result from a system's complexity using exact solutions for the PDF of the Fractional Kinetic Theory (FKT). Complexity theory is shown to be incompatible with Newton's unquestioning reliance on an absolute space and time upon which he built his discrete calculus.