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We propose a model to represent the motility of social elements. The model is completely deterministic, possesses a small number of parameters, and exhibits a series of properties that are reminiscent of the behavior of comunities in social-ecological competition; these are: (i) similar individuals attract each other; (ii) individuals can form stable groups; (iii) a group of similar individuals breaks into subgroups if it reaches a critical size; (iv) interaction between groups can modify the distribution of the elements as a result of fusion, fission, or pursuit; (v) individuals can change their internal state by interaction with their neighbors. The simplicity of the model and its richness of emergent behaviors, such as, for example, pursuit between groups, make it a useful toy model to explore a diversity of situations by changing the rule by which the internal state of individuals is modified by the interactions with the environment.
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We study the consequences of introducing individual nonconformity in social interactions, based on Axelrods model for the dissemination of culture. A constraint on the number of situations in which interaction may take place is introduced in order to lift the unavoidable ho mogeneity present in the final configurations arising in Axelrods related models. The inclusion of this constraint leads to the occurrence of complex patterns of intracultural diversity whose statistical properties and spatial distribution are characterized by means of the concepts of cultural affinity and cultural cli ne. It is found that the relevant quantity that determines the properties of intracultural diversity is given by the fraction of cultural features that characterizes the cultural nonconformity of individuals.
Social networks exhibit strikingly systematic patterns across a wide range of human contexts. While genetic variation accounts for a significant portion of the variation in many complex social behaviors, the heritability of egocentric social network attributes is unknown. Here we show that three of these attributes (in-degree, transitivity, and centrality) are heritable. We then develop a mirror network method to test extant network models and show that none accounts for observed genetic variation in human social networks. We propose an alternative Attract and Introduce model with two simple forms of heterogeneity that generates significant heritability as well as other important network features. We show that the model is well suited to real social networks in humans. These results suggest that natural selection may have played a role in the evolution of social networks. They also suggest that modeling intrinsic variation in network attributes may be important for understanding the way genes affect human behaviors and the way these behaviors spread from person to person.
The process of social expansion in Europe can be better understood with various concepts related to complexity science. Findings of exploratory research show a typical process of social expansion in Europe within the period 1495-1945, in which wars have been instrumental. Furthermore, this research enables the identification of vulnerabilities, and conditions for success in a process of social expansion.
We study the primacy in the Bulgarian urban system. Two groups of cities are studied: (i) the whole Bulgaria city system that contains about 250 cities and is studied in the time interval between 2004 and 2011; and (ii) A system of 33 cities, studied over the time interval 1887 till 2010. For these cities the 1946 population was over $10 000$ inhabitants. The notion of primacy in the two systems of cities is studied first from the global primacy index of Sheppard [$^1$]. Several (new) additional indices are introduced in order to compensate defects in the Sheppard index. Numerical illustrations are illuminating through the so called length ratio.
We note that the social inequality, represented by the Lorenz function obtained plotting the fraction of wealth possessed by the faction of people (starting from the poorest in an economy), or the plot or function representing the citation numbers against the respective number of papers by a scientist (starting from the highest cited paper in scientometrics), captured by the corresponding inequality indices (namely the Kolkata $k$ and the Hirsch $h$ indices respectively), are given by the fixed points of these nonlinear functions. It has been shown that under extreme competitions (in the markets or in the universities), the $k$ index approaches to an universal limiting value, as the dynamics of competition progresses. We introduce and study these indices for the inequalities of (pre-failure) avalanches (obtainable from ultrasonic emissions), given by their nonlinear size distributions in the Fiber Bundle Models (FBM) of non-brittle materials. We will show how a prior knowledge of this terminal and (almost) universal value of the $k$ index (for a range of values of the Weibull modulus characterizing the disorder, and also for uniformly dispersed disorder, in the FBM) for avalanche distributions (as the failure dynamics progresses) can help predicting the point (stress) or time (for uniform increasing rate of stress) for complete failure of the bundle. This observation has also been complemented by noting a similar (but not identical) behavior of the Hirsch index ($h$), redefined for such avalanche statistics.
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