Department of Humanities, Social and Political Sciences, ETH Zurich, Zurich, Switzerland.
PLoS One. 2010 Dec 9;5(12):e15210. doi: 10.1371/journal.pone.0015210.
We study evolutionary games in real social networks, with a focus on coordination games. We find that populations fail to coordinate in the same behavior for a wide range of parameters, a novel phenomenon not observed in most artificial model networks. We show that this result arises from the relevance of correlations beyond the first neighborhood, in particular from topological traps formed by links between nodes of different degrees in regions with few or no redundant paths. This specificity of real networks has not been modeled so far with synthetic networks. We thus conclude that model networks must be improved to include these mesoscopic structures, in order to successfully address issues such as the emergence of cooperation in real societies. We finally show that topological traps are a very generic phenomenon that may arise in very many different networks and fields, such as opinion models, spread of diseases or ecological networks.
我们在真实社交网络中研究演化博弈，重点关注协调博弈。我们发现，在广泛的参数范围内，群体无法协调到相同的行为，这是在大多数人工模型网络中没有观察到的新现象。我们表明，这一结果源于超越第一邻域的相关性，特别是由具有很少或没有冗余路径的区域中不同度数节点之间的连接形成的拓扑陷阱所致。到目前为止，这种真实网络的特殊性还没有被合成网络建模。因此，我们得出结论，模型网络必须加以改进，以纳入这些介观结构，以便成功解决现实社会中合作的出现等问题。最后，我们表明拓扑陷阱是一种非常普遍的现象，可能出现在许多不同的网络和领域中，如意见模型、疾病传播或生态网络。
