2,826 research outputs found

    Signed Networks, Triadic Interactions and the Evolution of Cooperation

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    We outline a model to study the evolution of cooperation in a population of agents playing the prisoner's dilemma in signed networks. We highlight that if only dyadic interactions are taken into account, cooperation never evolves. However, when triadic considerations are introduced, a window of opportunity for emergence of cooperation as a stable behaviour emerges.Comment: In Proceedings Wivace 2013, arXiv:1309.712

    Multirelational Organization of Large-scale Social Networks in an Online World

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    The capacity to collect fingerprints of individuals in online media has revolutionized the way researchers explore human society. Social systems can be seen as a non-linear superposition of a multitude of complex social networks, where nodes represent individuals and links capture a variety of different social relations. Much emphasis has been put on the network topology of social interactions, however, the multi-dimensional nature of these interactions has largely been ignored in empirical studies, mostly because of lack of data. Here, for the first time, we analyze a complete, multi-relational, large social network of a society consisting of the 300,000 odd players of a massive multiplayer online game. We extract networks of six different types of one-to-one interactions between the players. Three of them carry a positive connotation (friendship, communication, trade), three a negative (enmity, armed aggression, punishment). We first analyze these types of networks as separate entities and find that negative interactions differ from positive interactions by their lower reciprocity, weaker clustering and fatter-tail degree distribution. We then proceed to explore how the inter-dependence of different network types determines the organization of the social system. In particular we study correlations and overlap between different types of links and demonstrate the tendency of individuals to play different roles in different networks. As a demonstration of the power of the approach we present the first empirical large-scale verification of the long-standing structural balance theory, by focusing on the specific multiplex network of friendship and enmity relations.Comment: 7 pages, 5 figures, accepted for publication in PNA

    Triadic balance and closure as drivers of the evolution of cooperation

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    The prevalence of human cooperation continues to be one of the biggest puzzles for scientists. Structured interactions and clustering of cooperators are recognized mechanisms that help the dissemination of cooperative behavior. We analyze two dynamic micro structural mechanisms that may contribute to the evolution of cooperation. We concentrate on two mechanisms that have empirical justification: triadic closure and triadic balance. We study their relative efficiency under different parametric conditions, assuming that the structure of interactions itself might change endogenously as a result of previous encounters

    Triadic Balance and Closure as Drivers of the Evolution of Cooperation

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    https://ddd.uab.cat/pub/poncom/2014/128524/ssc14_a2014a92iENG.pdfThe prevalence of human cooperation continues to be one of the biggest puzzles for scientists. Structured interactions and clustering of cooperators are recognized mechanisms that help the dissemination of cooperative behavior. We analyze two dynamic micro structural mechanisms that may contribute to the evolution of cooperation. We concentrate on two mechanisms that have empirical justification: triadic closure and triadic balance. We study their relative efficiency under different parametric conditions, assuming that the structure of interactions itself might change endogenously as a result of previous encounters.The prevalence of human cooperation continues to be one of the biggest puzzles for scientists. Structured interactions and clustering of cooperators are recognized mechanisms that help the dissemination of cooperative behavior. We analyze two dynamic micro structural mechanisms that may contribute to the evolution of cooperation. We concentrate on two mechanisms that have empirical justification: triadic closure and triadic balance. We study their relative efficiency under different parametric conditions, assuming that the structure of interactions itself might change endogenously as a result of previous encounters

    Coupled dynamics of node and link states in complex networks: A model for language competition

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    Inspired by language competition processes, we present a model of coupled evolution of node and link states. In particular, we focus on the interplay between the use of a language and the preference or attitude of the speakers towards it, which we model, respectively, as a property of the interactions between speakers (a link state) and as a property of the speakers themselves (a node state). Furthermore, we restrict our attention to the case of two socially equivalent languages and to socially inspired network topologies based on a mechanism of triadic closure. As opposed to most of the previous literature, where language extinction is an inevitable outcome of the dynamics, we find a broad range of possible asymptotic configurations, which we classify as: frozen extinction states, frozen coexistence states, and dynamically trapped coexistence states. Moreover, metastable coexistence states with very long survival times and displaying a non-trivial dynamics are found to be abundant. Interestingly, a system size scaling analysis shows, on the one hand, that the probability of language extinction vanishes exponentially for increasing system sizes and, on the other hand, that the time scale of survival of the non-trivial dynamical metastable states increases linearly with the size of the system. Thus, non-trivial dynamical coexistence is the only possible outcome for large enough systems. Finally, we show how this coexistence is characterized by one of the languages becoming clearly predominant while the other one becomes increasingly confined to "ghetto-like" structures: small groups of bilingual speakers arranged in triangles, with a strong preference for the minority language, and using it for their intra-group interactions while they switch to the predominant language for communications with the rest of the population.Comment: 21 pages, 15 figure

    Degree Variance and Emotional Strategies Catalyze Cooperation in Dynamic Signed Networks

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    We study the problem of the emergence of cooperation in dynamic signed networks where agent strategies coevolve with relational signs and network topology. Running simulations based on an agent-based model, we compare results obtained in a regular lattice initialization with those obtained on a comparable random network initialization. We show that the increased degree heterogeneity at the outset enlarges the parametric conditions in which cooperation survives in the long run. Furthermore, we show how the presence of sign-dependent emotional strategies catalyze the evolution of cooperation with both network topology initializations.Comment: 16 Pages, Proceeding of the European Conference on Modelling and Simumatio

    Measuring social dynamics in a massive multiplayer online game

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    Quantification of human group-behavior has so far defied an empirical, falsifiable approach. This is due to tremendous difficulties in data acquisition of social systems. Massive multiplayer online games (MMOG) provide a fascinating new way of observing hundreds of thousands of simultaneously socially interacting individuals engaged in virtual economic activities. We have compiled a data set consisting of practically all actions of all players over a period of three years from a MMOG played by 300,000 people. This large-scale data set of a socio-economic unit contains all social and economic data from a single and coherent source. Players have to generate a virtual income through economic activities to `survive' and are typically engaged in a multitude of social activities offered within the game. Our analysis of high-frequency log files focuses on three types of social networks, and tests a series of social-dynamics hypotheses. In particular we study the structure and dynamics of friend-, enemy- and communication networks. We find striking differences in topological structure between positive (friend) and negative (enemy) tie networks. All networks confirm the recently observed phenomenon of network densification. We propose two approximate social laws in communication networks, the first expressing betweenness centrality as the inverse square of the overlap, the second relating communication strength to the cube of the overlap. These empirical laws provide strong quantitative evidence for the Weak ties hypothesis of Granovetter. Further, the analysis of triad significance profiles validates well-established assertions from social balance theory. We find overrepresentation (underrepresentation) of complete (incomplete) triads in networks of positive ties, and vice versa for networks of negative ties...Comment: 23 pages 19 figure

    Inductive Game Theory and the Dynamics of Animal Conflict

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    Conflict destabilizes social interactions and impedes cooperation at multiple scales of biological organization. Of fundamental interest are the causes of turbulent periods of conflict. We analyze conflict dynamics in an monkey society model system. We develop a technique, Inductive Game Theory, to extract directly from time-series data the decision-making strategies used by individuals and groups. This technique uses Monte Carlo simulation to test alternative causal models of conflict dynamics. We find individuals base their decision to fight on memory of social factors, not on short timescale ecological resource competition. Furthermore, the social assessments on which these decisions are based are triadic (self in relation to another pair of individuals), not pairwise. We show that this triadic decision making causes long conflict cascades and that there is a high population cost of the large fights associated with these cascades. These results suggest that individual agency has been over-emphasized in the social evolution of complex aggregates, and that pair-wise formalisms are inadequate. An appreciation of the empirical foundations of the collective dynamics of conflict is a crucial step towards its effective management

    Statistical physics of balance theory

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    Triadic relationships are accepted to play a key role in the dynamics of social and political networks. Building on insights gleaned from balance theory in social network studies and from Boltzmann-Gibbs statistical physics, we propose a model to quantitatively capture the dynamics of the four types of triadic relationships in a network. Central to our model are the triads’ incidence rates and the idea that those can be modeled by assigning a specific triadic energy to each type of triadic relation. We emphasize the role of the degeneracy of the different triads and how it impacts the degree of frustration in the political network. In order to account for a persistent form of disorder in the formation of the triadic relationships, we introduce the systemic variable temperature. In order to learn about the dynamics and motives, we propose a generic Hamiltonian with three terms to model the triadic energies. One term is connected with a three-body interaction that captures balance theory. The other terms take into account the impact of heterogeneity and of negative edges in the triads. The validity of our model is tested on four datasets including the time series of triadic relationships for the standings between two classes of alliances in a massively multiplayer online game (MMOG). We also analyze real-world data for the relationships between the “agents” involved in the Syrian civil war, and in the relations between countries during the Cold War era. We find emerging properties in the triadic relationships in a political network, for example reflecting itself in a persistent hierarchy between the four triadic energies, and in the consistency of the extracted parameters from comparing the model Hamiltonian to the data

    Networks of Influence: Implementing Politically Sustainable Multinational Stakeholder Strategies

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    In a bid to gain stakeholder support for their operations, multinational firms operating in politically uncertain environments often inappropriately apply a rational financial approach to a sociopolitical problem. Using the tools of network theory, I present an alternative sociopolitical approach to gaining stakeholder support by engendering cooperative relations and increasing tie formation while minimizing conflict. This dissertation comprises three paper chapters. The first, theory, paper chapter outlines a theory of influence exploring how the firm\u27s strategic position within the network of stakeholders affords it positional benefits of information and reputation, while also highlighting the costs of exposure to pre-existing conflict and the fostering of conflict through asymmetric relations. The second, empirical, paper chapter explores how firms can best manage altercentric and egocentric uncertainty in the nonmarket environment and compares the efficacy of the ex ante strategies that the firm can use to manage both types of uncertainty. I hypothesize and find that through strategic network positioning that affords it information, the firm can manage its egocentric uncertainty; and, by managing how it is perceived through its associations, the firm can also manage stakeholders\u27 altercentric uncertainty. When both strategies are assessed together, I find greater returns to firms in terms of engendering cooperation, minimizing conflict and forming ties by managing altercentric uncertainty through strategic associations. In the third, also empirical, paper chapter, I use insights from structural balance theory to explore the relationship between dyadic structure and triadic closure among networks of actors in the sociopolitical context. I outline and test hypotheses of four types of structural homophily of the actors in the triad—access to resources, status, likeability and number of ties (popularity)—on the likelihood of the closure of that triad. I find that a link that closes an open directed triad is more likely when the actors of the triad have different access to resources, different status, and similar numbers of ties to other actors. I also find that likeability among actors in the triad has no impact on the likelihood of closing that triad. My empirical papers test the relationships among firms and stakeholders in a novel hand-coded database of 51,754 stakeholder events linking 4,623 unique stakeholders of a population of 19 publicly traded gold mining firms which operate 26 mines in 20 largely emerging economies
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