标题： 识别社区网络上流行病的有影响力传播者 显示英文标题

标题： Identifying Influential Spreaders of Epidemics on Community Networks

摘要： 一种用于识别可能用于控制种群内流行病的有影响力的传播者的高效策略将具有相当重要的意义。 一般来说，种群由其社区结构以及跨越社区的节点之间的弱联系的异质分布所表征。 这里提出了一种针对社区网络的策略，能够识别加速疾病传播的有影响力传播者。 在此策略中，有影响力传播者作为目标节点。 这是基于这样一个想法：在k-shell分解中，弱联系和强联系是分别处理的。 该策略被应用于从在线社交网络构建的经验网络上，结果表明该策略比其他策略更准确。 它的有效性源于邻居之间的连通性模式，并成功识别了重要节点。 此外，即使在网络结构存在错误的情况下，该策略的表现依然稳健。 显示英文摘要

摘要： An efficient strategy for the identification of influential spreaders that could be used to control epidemics within populations would be of considerable importance. Generally, populations are characterized by its community structures and by the heterogeneous distributions of weak ties among nodes bridging over communities. A strategy for community networks capable of identifying influential spreaders that accelerate the spread of disease is here proposed. In this strategy, influential spreaders serve as target nodes. This is based on the idea that, in k-shell decomposition, weak ties and strong ties are processed separately. The strategy was used on empirical networks constructed from online social networks, and results indicated that this strategy is more accurate than other strategies. Its effectiveness stems from the patterns of connectivity among neighbors, and it successfully identified the important nodes. In addition, the performance of the strategy remained robust even when there were errors in the structure of the network.