Department of Physics, College of Computer and Information Sciences, Department of Health Sciences, Northeastern University, Boston, MA 02115, USA.
Sci Rep. 2012;2:469. doi: 10.1038/srep00469. Epub 2012 Jun 25.
Network modeling plays a critical role in identifying statistical regularities and structural principles common to many systems. The large majority of recent modeling approaches are connectivity driven. The structural patterns of the network are at the basis of the mechanisms ruling the network formation. Connectivity driven models necessarily provide a time-aggregated representation that may fail to describe the instantaneous and fluctuating dynamics of many networks. We address this challenge by defining the activity potential, a time invariant function characterizing the agents' interactions and constructing an activity driven model capable of encoding the instantaneous time description of the network dynamics. The model provides an explanation of structural features such as the presence of hubs, which simply originate from the heterogeneous activity of agents. Within this framework, highly dynamical networks can be described analytically, allowing a quantitative discussion of the biases induced by the time-aggregated representations in the analysis of dynamical processes.
网络建模在识别许多系统共有的统计规律和结构原则方面起着至关重要的作用。绝大多数最近的建模方法都是基于连接性的。网络的结构模式是支配网络形成的机制的基础。连接驱动的模型必然提供一个时间聚合的表示，可能无法描述许多网络的瞬时和波动动态。我们通过定义活动势能来解决这个挑战，这是一个时间不变的函数，用于描述代理之间的相互作用，并构建一个活动驱动的模型，能够编码网络动态的瞬时时间描述。该模型提供了对结构特征的解释，例如集线器的存在，这仅仅源于代理的异质活动。在这个框架内，可以对高度动态的网络进行分析，从而可以对在动态过程分析中时间聚合表示所产生的偏差进行定量讨论。
