Month: June 2022

Nutrient concentrations in food display universal behaviour

Giulia Menichetti & Albert-László Barabási 

Nature Food volume 3, pages375–382 (2022)

Extensive programmes around the world endeavour to measure and catalogue the composition of food. Here we analyse the nutrient content of the full US food supply and show that the concentration of each nutrient follows a universal single-parameter scaling law that accurately captures the eight orders of magnitude in nutrient content variability. We show that the universality is rooted in the biochemical constraints obeyed by the metabolic pathways responsible for nutrient modulation, allowing us to confirm the empirically observed scaling law and to predict its variability in agreement with the data. We propose that the natural nutrient variability in food can be quantitatively formalized. This provides a mathematical rationale for imputing missing values in food composition databases and paves the way towards a quantitative understanding of the impact of food processing on nutrient balance and health effects.

Read the full article at: www.nature.com

The emergence of polarization in coevolving networks

Jiazhen Liu, Shengda Huang, Nathan Aden, Neil Johnson, Chaoming Song
Polarization is a ubiquitous phenomenon in social systems. Empirical studies show substantial evidence for opinion polarization across social media. Recent modeling works show qualitatively that polarization emerges in coevolving networks by integrating reinforcing mechanisms and network evolution. However, a quantitative and comprehensive theoretical framework capturing generic mechanisms governing polarization remains unaddressed. In this paper, we discover a universal scaling law for opinion distributions, characterized by a set of scaling exponents. These exponents classify social systems into polarization and depolarization phases. We find two generic mechanisms governing the polarization dynamics, and propose a coevolving framework that counts for opinion dynamics and network evolution simultaneously. We show analytically three different phases including polarization, partial polarization, and depolarization, and the corresponding phase diagram. In the polarized phase, our theory predicts that a bi-polarized community structure emerges naturally from the coevolving dynamics. These theoretical predictions are in line with observations in empirical datasets. Our theory not only accounts for the empirically observed scaling laws but also allows us to quantitatively predict scaling exponents.

Read the full article at: arxiv.org

Group mixing drives inequality in face-to-face gatherings

Marcos Oliveira, Fariba Karimi, Maria Zens, Johann Schaible, Mathieu Génois & Markus Strohmaier
Communications Physics volume 5, Article number: 127 (2022)

Uncovering how inequality emerges from human interaction is imperative for just societies. Here we show that the way social groups interact in face-to-face situations can enable the emergence of disparities in the visibility of social groups. These disparities translate into members of specific social groups having fewer social ties than the average (i.e., degree inequality). We characterize group degree inequality in sensor-based data sets and present a mechanism that explains these disparities as the result of group mixing and group-size imbalance. We investigate how group sizes affect this inequality, thereby uncovering the critical size and mixing conditions in which a critical minority group emerges. If a minority group is larger than this critical size, it can be a well-connected, cohesive group; if it is smaller, minority cohesion widens inequality. Finally, we expose group under-representation in degree rankings due to mixing dynamics and propose a way to reduce such biases. The emergence of inequality in social interactions can depend on a number of factors, among which the intrinsic attractiveness of individuals, but also group size the presence of pre-formed social ties. Here, the authors propose “social attractiveness” as a mechanism to account for the emergence of inequality in face-to-face social dynamics and show this reproduces real-world gathering data, predicting the existence of a critical group size for the minority group below which higher cohesion among its members leads to higher inequality.

Read the full article at: www.nature.com