Spreads can be contained through tuning the underlying contact networks, such as the
social distance policy reducing the average degree of social contacts and the suspension of …

A common network inference problem, arising from real-world data constraints, is how to
infer a dynamic network from its time-aggregated adjacency matrix and time-varying …

Online social networks facilitate the spread of information, while rumors can also propagate
widely and fast, which may mislead some users. Therefore, suppressing the spread of …

Graph learning (GL) models have been applied in various predictive tasks on graph data.
But, similarly to other machine learning models, GL models are also vulnerable to …

The misinformation prevention (MP) problem, which aims to find anchor nodes (P-seeds) to
start an anti-spread of positive information, has attracted abundant research attention due to …

Understanding and mitigating epidemic spread in complex networks requires the
measurement of structural network properties associated with epidemic risk. Classic …

We address the emerging challenge of school segregation within the context of free school
choice systems. Households take into account both proximity and demographic composition …

Despite the numerous ways now available to quantify which parts or subsystems of a
network are most important, there remains a lack of centrality measures that are related to …

异常传播是当今在线社交网络中频繁出现的一种非传统的信息传播模式. 为了完整地认知社交
网络中异常传播的整体过程, 将异常传播生命周期系统归纳为潜伏期, 扩散期, 高潮期和衰退期4 …

Online social networks serve as a very important platform for information dissemination in
reality. In addition to the positive information, negative information such as all kinds of …