Network science provides theoretical, computational, and empirical tools that can be used to
understand the structure and function of the human brain in novel ways using simple …

Some brain regions have a central role in supporting integrated brain function, marking them
as network hubs. Given the functional importance of hubs, it is natural to ask how they …

Centrality is one of the most studied concepts in social network analysis. There is a huge
literature regarding centrality measures, as ways to identify the most relevant users in a …

The roles of different nodes within a network are often understood through centrality
analysis, which aims to quantify the capacity of a node to influence, or be influenced by …

Relationships and the pattern of relationships have a large and varied influence on both
individual and group action. The fundamental distinction of social network analysis research …

Despite growing attention to corporate social-political advocacy, little is known about how
publics mobilize and establish relationships in social media when firms are involved in hot …

We show that prominent centrality measures in network analysis are all based on additively
separable and linear treatments of statistics that capture a node's position in the network …

Can we identify highly central individuals in a network without collecting network data,
simply by asking community members? Can seeding information via such nominated …

In complex networks, each node has some unique characteristics that define the importance
of the node based on the given application-specific context. These characteristics can be …

This study applied the question-oriented problem-solving (QOPS) pedagogy in Statistics
learning and addressed several methodological and theoretical gaps in SNA studies to …