On the other hand, we detect the presence of a very important exception.
However, our analysis has shown that for various indices of sociopolitical destabilization this curvilinear relationship can be quite different in some important details. Our empirical tests generally support the hypothesis that up to certain values of the average per capita income its growth tends to lead to increased risks of sociopolitical destabilization, and only in the upper range of this indicator its growth tends to be associated with the decrease of sociopolitical destabilization risks. Moreover, we support our WBPA model with a socio-psychological interpretation, that offers a deeper understanding of the mechanics behind social network dynamics. Consequently, as node betweenness proves to be paramount to attracting new links - as well as strengthening existing links -, we propose the new Weighted Betweenness Preferential Attachment (WBPA) model, which renders quantitatively robust results on realistic network metrics. In this paper, we explore the distribution of social network parameters and centralities and argue that node degree is not the main attractor of new social links. Indeed, important properties such as dynamic community formation, link weight evolution, or degree saturation cannot be completely and simultaneously described by state of the art models. While certain real-world properties are captured by the degree-driven preferential attachment model, it still cannot fully explain social network dynamics. The dynamics of social networks is a complex process, as there are many factors which contribute to the formation and evolution of social links.
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