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| 1 | Higher-order temporal interactions promote the cooperation in the multiplayer snowdrift game显示文摘To explore evolutionary dynamics of collective behaviors within the interconnected population,previous studies usually map non-pairwise interactions to higher-order static networks.However,from human communications to chemical reactions and biological systems,interactions often change over time,which cannot be simply described by higher-order static networks.In this study,we introduce time effects into higher-order networks and correspondingly investigate the evolutionary dynamics of multiplayer snowdrift games on higher-order temporal networks.Specifically,extensive simulations from four empirical datasets reveal that(1)the temporal effect of higher-order networks can facilitate the evolution of cooperation;(2)the higher-order topology can enhance the emergence of cooperation within a certain range of parameters;(3)the contribution of temporal burstiness and participants burstiness to cooperation is reversed.Furthermore,we theoretically demonstrate that the higher-order structure will suppress the propagation of defection in temporal networks.Our findings offer a new avenue for studying the evolution of altruistic behaviors in realistic complex networks. | Yan XU Juan WANG Chengyi XIA Zhen WANG | 2023 | Science China(Information Sciences)2023，66，12： | 0 |
| 2 | Exploring link generation in a temporal evolution network for human mobility显示文摘The prevalence of mobile devices has spurred human mobility to be applied in mobile networking and communications by using network science, in which the temporal evolution of a network topology is of great importance for protocol design and performance analysis. This paper focuses on link generation in a temporal evolution network. Based on observations revealing the strong correlation between the connection patterns of different time periods, a link generation potential based on historical connections is proposed in this paper, aiming to provide a method for making topological predictions with less randomness. Using MIT Reality dataset, an evaluation of the accuracy of the proposed method was conducted. The experimental results demonstrate the proposal's adequacy in terms of its accuracy. | SHI Yan SUN WangDong CHEN Bin ZHOU XiaoJuan CHEN ShanZhi WANG ShengFeng | 2016 | Science China(Technological Sciences)2016，59，1： | 0 |
| 3 | A dynamic influence model of social network hotspot based on grey system显示文摘The outbreak of hotspot in social network may contain complex dynamic genesis. Using user behavior data from hotspots in social network, we study how different user groups play different roles for a hotspot topic. Firstly, by analyzing users' behavior records, we mine group situation that promotes the hotspot.Several major attributions in a hotspot outbreak, such as individual, peer and group triggers, are defined formally according to the view-point of social identity, social interaction, retweet depth and opinion leader. Secondly,for the problem of the uneven and sparse data in each stage of hotspot topic's life cycle, we propose a dynamic influence model based on grey system to formalize the effect of different groups. Then the process of hotspot evolution driven by distinct crowd is showed dynamically. The experimental result confirms that the model is able not only to qualify users' influence on a hotspot topic but also to predict effectively an upcoming change in a hotspot topic. | XIAO YunPeng MA Jing LIU YanBing YAN ZhiXian | 2015 | Science China Chemistry2015，58，12： | 0 |
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