We study the evolutionary Prisoner's Dilemma on two social networks substrates obtained from actual relational data. We find very different cooperation levels on each of them that cannot be easily understood in terms of global statistical properties of both networks. We claim that the result can be understood at the mesoscopic scale, by studying the community structure of the networks. We explain the dependence of the cooperation level on the temptation parameter in terms of the internal structure of the communities and their interconnections. We then test our results on community-structured, specifically designed artificial networks, finding a good agreement with the observations in both real substrates. Our results support the conclusion that studies of evolutionary games on model networks and their interpretation in terms of global properties may not be sufficient to study specific, real social systems. Further, the study allows us to define new quantitative parameters that summarize the mesoscopic structure of any network. In addition, the community perspective may be helpful to interpret the origin and behavior of existing networks as well as to design structures that show resilient cooperative behavior.

Nobel Prizes are commonly seen to be among the most prestigious achievements of our times. Based on mining several million citations, we quantitatively analyze the processes driving paradigm shifts in science. We find that groundbreaking discoveries of Nobel Prize Laureates and other famous scientists are not only acknowledged by many citations of their landmark papers. Surprisingly, they also boost the citation rates of their previous publications. Given that innovations must outcompete the rich-gets-richer effect for scientific citations, it turns out that they can make their way only through citation cascades. A quantitative analysis reveals how and why they happen. Science appears to behave like a self-organized critical system, in which citation cascades of all sizes occur, from continuous scientific progress all the way up to scientific revolutions, which change the way we see our world. Measuring the “boosting effect” of landmark papers, our analysis reveals how new ideas and new players can make their way and finally triumph in a world dominated by established paradigms. The underlying “boost factor” is also useful to discover scientific breakthroughs and talents much earlier than through classical citation analysis, which by now has become a widespread method to measure scientific excellence, influencing scientific careers and the distribution of research funds. Our findings reveal patterns of collective social behavior, which are also interesting from an attention economics perspective. Understanding the origin of scientific authority may therefore ultimately help to explain how social influence comes about and why the value of goods depends so strongly on the attention they attract.

Many natural and artificial two-states signaling devices are connected forming networks. The information-processing potential of these systems is usually related to the response to weak external signals. Here, using a network of overdamped bistable elements, we study the effect of a heterogeneous complex topology on the signal response. The analysis of the problem in random scale-free networks, reveals that heterogeneity plays a crucial role in amplifying external signals. We have contrasted numerical simulations with analytical calculations in simplified topologies.

Social learning, as an information acquisition process, enables intergenerational transmission and the stabilisation of cultural forms, generating and sustaining behavioural traditions within human groups. Archaeologically, such social processes might become observable by identifying repetitions in the record that result from the execution of standardised actions. From a zooarchaeological perspective, the processing and consumption of carcasses may be used to identify these types of phenomena at the sites. To investigate this idea, several faunal assemblages from Bolomor Cave (Valencia, Spain, MIS 9-5e) and Gran Dolina TD10-1 (Burgos, Spain, MIS 9) were analysed. The data show that some butchery activities exhibit variability as a result of multiple conditioning factors and, therefore, the identification of cultural patterns through the resulting cut-marks presents additional difficulties. However, other activities, such as marrow removal by means of intentional breakage, seem to reflect standardised actions unrelated to the physical characteristics of the bones. The statistical tests we applied show no correlation between the less dense areas of the bones and the location of impacts. Comparison of our experimental series with the archaeological samples indicates a counter-intuitive selection of the preferred locus of impact, especially marked in the case of Bolomor IV. This fact supports the view that bone breakage was executed counter-intuitively and repetitively on specific sections because it may have been part of an acquired behavioural repertoire. These reiterations differ between levels and sites, suggesting the possible existence of cultural identities or behavioural predispositions dependant on groups. On this basis, the study of patterns could significantly contribute to the identification of occupational strategies and organisation of the hominids in a territory. In this study, we use faunal data in identifying the mechanics of intergenerational information transmission within Middle Pleistocene human communities and provide new ideas for the investigation of occupational dynamics from a zooarchaeological approach.