Homophily-Based Social Group Formation in a Spin Glass Self-Assembly Framework

Dislike of general opinion makes for tight elections

In modern democracies, the outcome of elections and referendums is often remarkably tight. The repetition of these divisive events are the hallmark of a split society; to the physicist, however, it is an astonishing feat for such large collections of diverse individuals. Many sociophysics models reproduce the emergence of collective human behavior with interacting agents, which respond to their environment according to simple rules, modulated by random fluctuations. A paragon of this class is the Ising model which, when interactions are strong, predicts that order can emerge from a chaotic initial state. In contrast with many elections, however, this model favors a strong majority. Here we introduce a new element to this classical theory, which accounts for the influence of opinion polls on the electorate. This brings about a new phase in which two groups divide the opinion equally. These political camps are spatially segregated, and the sharp boundary that separates them makes the system size dependent, even in the limit of a large electorate. Election data show that, since the early 1990s, countries with more than about a million voters often found themselves in this state, whereas elections in smaller countries yielded more consensual results. We suggest that this transition hinges on the electorate's awareness of the general opinion.

New Forms of Collaboration Between the Social and Natural Sciences Could Become Necessary for Understanding Rapid Collective Transitions in Social Systems

Human societies are complex systems and as such have tipping points. They can rapidly transit from one mode of operation to another and thereby change the way they function as a whole. Such transitions appear as financial or economic crises, rapid swings in collective opinion, political regime shifts, or revolutions. In physics collective transitions are known as phase transitions; for example, water exists in states of liquid, ice, and vapor. A few variables determine which state is realized: temperature, pressure, and volume. For social systems it is less clear what determines collective social states. A better understanding of social tipping points would allow us to tackle some of the big challenges more systematically, such as polarization, loss of social cohesion, fragmentation, or the green transition. The physics concept of universality might be key to understanding some tipping points in human societies and why agent-based models (ABMs) might make sense for identifying the transition points. If universality exists in social systems there is hope that relatively simple ABMs will be sufficient for understanding collective social systems in transition; if it does not exist, highly detailed computational models will be unavoidable. Both are possible. Both need new forms of collaboration between the social and natural sciences, and new types of data will be essential.

Sandpile Universality in Social Inequality: Gini and Kolkata Measures

Social inequalities are ubiquitous and evolve towards a universal limit. Herein, we extensively review the values of inequality measures, namely the Gini (g) index and the Kolkata (k) index, two standard measures of inequality used in the analysis of various social sectors through data analysis. The Kolkata index, denoted as k, indicates the proportion of the 'wealth' owned by (1-k) fraction of the 'people'. Our findings suggest that both the Gini index and the Kolkata index tend to converge to similar values (around g=k≈0.87, starting from the point of perfect equality, where g=0 and k=0.5) as competition increases in different social institutions, such as markets, movies, elections, universities, prize winning, battle fields, sports (Olympics), etc., under conditions of unrestricted competition (no social welfare or support mechanism). In this review, we present the concept of a generalized form of Pareto's 80/20 law (k=0.80), where the coincidence of inequality indices is observed. The observation of this coincidence is consistent with the precursor values of the g and k indices for the self-organized critical (SOC) state in self-tuned physical systems such as sand piles. These results provide quantitative support for the view that interacting socioeconomic systems can be understood within the framework of SOC, which has been hypothesized for many years. These findings suggest that the SOC model can be extended to capture the dynamics of complex socioeconomic systems and help us better understand their behavior.