Network science offers powerful tools to model complex social systems. Most social network
science research focuses on topological networks by simply considering the binary state of …

In the present-days complex networks modeled on real-world data contain millions of nodes
and billions of links. Identifying super spreaders in such an extensive network is a …

Understanding the complex process of information spread in online social networks (OSNs)
enables the efficient maximization/minimization of the spread of useful/harmful information …

Influence maximization is an important research problem in the field of network science
because of its business value. It requires the strategic selection of seed nodes called …

The identification of important nodes in complex networks has always been a prominent
topic in the field of network science. Nowadays, the emergence of large-scale networks has …

Measuring the importance of nodes is a rapidly developing field in network science, with
centrality measures playing a critical role in various applications, including epidemic control …

A corpus is a massive body of structured textual data that are stored and operated
electronically. It usually combines with statistics, machine learning algorithms, or artificial …

In this paper, we utilize network theory to model and study the coupled high-speed rail–
aviation network (HSR–AN) in China. The HSR–AN depicting the transport services is …

Proteins drive virtually all cellular-level processes. The proteins that are critical to cell
proliferation and survival are defined as essential. These essential proteins are implicated in …

Identifying influential nodes, with pivotal roles in practical domains like epidemic
management, social information dissemination optimization, and transportation network …