Mesoscopic structure conditions the emergence of cooperation on social networks

We study the evolutionary Prisoner's Dilemma on two social networks obtained from actual relational data. We find very different cooperation levels on each of them that can not 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 perfect agreement with the observations in the real networks. 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. 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.Comment: Largely improved version, includes an artificial network model that fully confirms the explanation of the results in terms of inter- and intra-community structur

Instability of supersymmetric microstate geometries

We investigate the classical stability of supersymmetric, asymptotically flat, microstate geometries with five non-compact dimensions. Such geometries admit an "evanescent ergosurface": a timelike hypersurface of infinite redshift. On such a surface, there are null geodesics with zero energy relative to infinity. These geodesics are stably trapped in the potential well near the ergosurface. We present a heuristic argument indicating that this feature is likely to lead to a nonlinear instability of these solutions. We argue that the precursor of such an instability can be seen in the behaviour of linear perturbations: nonlinear stability would require that all linear perturbations decay sufficiently rapidly but the stable trapping implies that some linear perturbation decay very slowly. We study this in detail for the most symmetric microstate geometries. By constructing quasinormal modes of these geometries we show that generic linear perturbations decay slower than any inverse power of time.This work was supported by European Research Council grant ERC-2011-StG279363-HiDGR.This is the final version of the article. It first appeared from Springer via https://doi.org/10.1007/JHEP10(2016)03

Interdependent network reciprocity in evolutionary games

Besides the structure of interactions within networks, also the interactions between networks are of the outmost importance. We therefore study the outcome of the public goods game on two interdependent networks that are connected by means of a utility function, which determines how payoffs on both networks jointly influence the success of players in each individual network. We show that an unbiased coupling allows the spontaneous emergence of interdependent network reciprocity, which is capable to maintain healthy levels of public cooperation even in extremely adverse conditions. The mechanism, however, requires simultaneous formation of correlated cooperator clusters on both networks. If this does not emerge or if the coordination process is disturbed, network reciprocity fails, resulting in the total collapse of cooperation. Network interdependence can thus be exploited effectively to promote cooperation past the limits imposed by isolated networks, but only if the coordination between the interdependent networks is not disturbe

Childhood obesity, thyroid function, and insulin resistance – is there a link? A longitudinal study

Serum thyroid stimulating hormone (TSH) levels are frequently elevated in obese children and are most likely to be associated with insulin resistance. However, clinical relevance of this association remains unclear. OBJECTIVES: To assess the prevalence of hyperthyrotropinemia; to analyze the relationship between TSH and homeostasis model assessment - insulin resistance (HOMA-IR); and to verify whether TSH levels and HOMA-IR vary with weight loss in obese children. SUBJECTS AND METHODS: Retrospective longitudinal study with data from baseline and 1 year after lifestyle intervention in a pediatric obese group (344 children were recruited and 100 among them completed follow-up). For postintervention analysis, three groups were considered according to body mass index-standard deviation score (BMI-SDS) variations: ≤-0.5 (significant weight loss); 0.5-0 (weight loss); and >0 (weight gain). Statistical analysis was performed using SPSS 19.0®. RESULTS: The prevalence of increased TSH levels was 9.3%. At baseline TSH (p=0.007), fT4 (p=0.006), and HOMA-IR (p<0.001) were positively correlated to BMI-SDS (n=344). Weight reduction was verified in 67 out of 100 cases but significant loss was present in only 21 cases. Decreases in both TSH and BMI-SDS were independently associated with decreases in HOMA-IR (p=0.005 and p=0.016, respectively). There was no correlation between TSH and BMI-SDS variation. Significant decreases in the HOMA-IR (p=0.006) were only achieved in the significant weight loss group. CONCLUSIONS: The prevalence of hyperthyrotropinemia was lower than previously reported. However, cutoff values were adjusted to pubertal stage, suggesting an over report in other studies. Insulin resistance and TSH were positively correlated, independent of body status. Although weight loss was not associated with TSH variation, a decrease in TSH levels was independently associated with decreases in HOMA-IR.info:eu-repo/semantics/publishedVersio

If players are sparse social dilemmas are too: Importance of percolation for evolution of cooperation

Spatial reciprocity is a well known tour de force of cooperation promotion. A thorough understanding of the effects of different population densities is therefore crucial. Here we study the evolution of cooperation in social dilemmas on different interaction graphs with a certain fraction of vacant nodes. We find that sparsity may favor the resolution of social dilemmas, especially if the population density is close to the percolation threshold of the underlying graph. Regardless of the type of the governing social dilemma as well as particularities of the interaction graph, we show that under pairwise imitation the percolation threshold is a universal indicator of how dense the occupancy ought to be for cooperation to be optimally promoted. We also demonstrate that myopic updating, due to the lack of efficient spread of information via imitation, renders the reported mechanism dysfunctional, which in turn further strengthens its foundations.Comment: 6 two-column pages, 5 figures; accepted for publication in Scientific Reports [related work available at http://arxiv.org/abs/1205.0541

Optimal interdependence between networks for the evolution of cooperation

Recent research has identified interactions between networks as crucial for the outcome of evolutionary games taking place on them. While the consensus is that interdependence does promote cooperation by means of organizational complexity and enhanced reciprocity that is out of reach on isolated networks, we here address the question just how much interdependence there should be. Intuitively, one might assume the more the better. However, we show that in fact only an intermediate density of sufficiently strong interactions between networks warrants an optimal resolution of social dilemmas. This is due to an intricate interplay between the heterogeneity that causes an asymmetric strategy flow because of the additional links between the networks, and the independent formation of cooperative patterns on each individual network. Presented results are robust to variations of the strategy updating rule, the topology of interdependent networks, and the governing social dilemma, thus suggesting a high degree of universality

Evolution of Cooperation and Coordination in a Dynamically Networked Society

Situations of conflict giving rise to social dilemmas are widespread in society and game theory is one major way in which they can be investigated. Starting from the observation that individuals in society interact through networks of acquaintances, we model the co-evolution of the agents' strategies and of the social network itself using two prototypical games, the Prisoner's Dilemma and the Stag Hunt. Allowing agents to dismiss ties and establish new ones, we find that cooperation and coordination can be achieved through the self-organization of the social network, a result that is non-trivial, especially in the Prisoner's Dilemma case. The evolution and stability of cooperation implies the condensation of agents exploiting particular game strategies into strong and stable clusters which are more densely connected, even in the more difficult case of the Prisoner's Dilemma.Comment: 18 pages, 14 figures. to appea

Wisdom of groups promotes cooperation in evolutionary social dilemmas

Whether or not to change strategy depends not only on the personal success of each individual, but also on the success of others. Using this as motivation, we study the evolution of cooperation in games that describe social dilemmas, where the propensity to adopt a different strategy depends both on individual fitness as well as on the strategies of neighbors. Regardless of whether the evolutionary process is governed by pairwise or group interactions, we show that plugging into the "wisdom of groups" strongly promotes cooperative behavior. The more the wider knowledge is taken into account the more the evolution of defectors is impaired. We explain this by revealing a dynamically decelerated invasion process, by means of which interfaces separating different domains remain smooth and defectors therefore become unable to efficiently invade cooperators. This in turn invigorates spatial reciprocity and establishes decentralized decision making as very beneficial for resolving social dilemmas.Comment: 8 two-column pages, 7 figures; accepted for publication in Scientific Report

Modeling Evolutionary Dynamics of Lurking in Social Networks

Lurking is a complex user-behavioral phenomenon that occurs in all large-scale online communities and social networks. It generally refers to the behavior characterizing users that benefit from the information produced by others in the community without actively contributing back to the production of social content. The amount and evolution of lurkers may strongly affect an online social environment, therefore understanding the lurking dynamics and identifying strategies to curb this trend are relevant problems. In this regard, we introduce the Lurker Game, i.e., a model for analyzing the transitions from a lurking to a non-lurking (i.e., active) user role, and vice versa, in terms of evolutionary game theory. We evaluate the proposed Lurker Game by arranging agents on complex networks and analyzing the system evolution, seeking relations between the network topology and the final equilibrium of the game. Results suggest that the Lurker Game is suitable to model the lurking dynamics, showing how the adoption of rewarding mechanisms combined with the modeling of hypothetical heterogeneity of users' interests may lead users in an online community towards a cooperative behavior.Comment: 13 pages, 5 figures. Accepted at CompleNet 201