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 …

Social network based applications have experienced exponential growth in recent years.
One of the reasons for this rise is that this application domain offers a particularly fertile …

Influence Maximization (IM), which selects a set of k users (called seed set) from a social
network to maximize the expected number of influenced users (called influence spread), is a …

Finding an optimal set of nodes, called key players, whose activation (or removal) would
maximally enhance (or degrade) a certain network functionality, is a fundamental class of …

Given a social network G and a positive integer k, the influence maximization problem asks
for k nodes (in G) whose adoptions of a certain idea or product can trigger the largest …

Google's PageRank method was developed to evaluate the importance of web-pages via
their link structure. The mathematics of PageRank, however, are entirely general and apply …

Given a social network G and a constant k, the influence maximization problem asks for k
nodes in G that (directly and indirectly) influence the largest number of nodes under a pre …

The ongoing rapid expansion of the Word Wide Web (WWW) greatly increases the
information of effective transmission from heterogeneous individuals to various systems …

Abstract As Big Data has undergone a transition from being an emerging topic to a growing
research area, it has become necessary to classify the different types of research and …

Diffusion is a fundamental graph process, underpinning such phenomena as epidemic
disease contagion and the spread of innovation by word-of-mouth. We address the …