Complex networks are ubiquitous: a cell, the human brain, a group of people and the
Internet are all examples of interconnected many-body systems characterized by …

Real networks exhibit heterogeneous nature with nodes playing far different roles in
structure and function. To identify vital nodes is thus very significant, allowing us to control …

The growth of social media has completely revamped the way people interact, communicate
and engage. These platforms play a key role in facilitating greater outreach and influence …

The dynamics and influence of fake news on Twitter during the 2016 US presidential
election remains to be clarified. Here, we use a dataset of 171 million tweets in the five …

Influence maximization is the process of identifying a small set of influential nodes from a
complex network to maximize the number of activation nodes. Due to the critical issues such …

Finding an optimal subset of nodes in a network that is able to efficiently disrupt the
functioning of a corrupt or criminal organization or contain an epidemic or the spread of …

The purpose of this research is to investigate the status and the evolution of the scientific
studies for the effect of social networks on big data and usage of big data for modeling the …

From physics to engineering, biology and social science, natural and artificial systems are
characterized by interconnected topologies whose features–eg, heterogeneous connectivity …

Centrality metrics have been studied in the network science research. They have been used
in various networks, such as communication, social, biological, geographic, or contact …

Almost all the complex interactions between humans, animals, biological cells, neurons, or
any other objects are now modeled as a graph with the nodes as the objects of interest and …