Community structure exists in most real-world networks, such as social networks, smart
grids, and transportation networks. Established approaches for community detection usually …

There are three types of social network users: ordinary users, opinion leaders, and structural
hole (SH) spanners. Opinion leaders and SH spanners are key circulators of information. SH …

Structural clustering (SCAN) is one of the most popular graph clustering paradigms.
However, SCAN assumes that the input graph is undirected and can not cluster the directed …

Modeling and exploring high-order connectivity patterns, also called network motifs, are
essential for understanding the fundamental structures that control and mediate the behavior …

Detecting and analyzing community structure is a challenging topic in dynamic social
network analysis. Although the number of methods in this area is on the rise, there are only a …

Community detection on social networks is a fundamental and crucial task in the research
field of social computing. Here we propose DSCPCD—a dual structural consistency …

Influential nodes in complex networks play more significant role than other nodes in many
applications such as viral marketing. Identification of the most influential nodes and ranking …

As an increasing amount of network data emerges, especially for online daily social
networks, a prominent question arises is how to observe the formed community structure. In …

Most of the existing studies measure the risk dependence between corporations based on
quantitative market data, which is susceptible to interference from market speculative …

Hybrid opinion dynamics which involves two types of individuals (ie, leaders and followers)
communicate in real time and share opinions and knowledge have been widely used in …