We propose a new centrality measure, called the Random Walk Decay centrality. While most centralities in the literature are based on the notion of shortest paths, this new centrality measure stems from the random walk on the network. We provide an axiomatic characterization and show that the new centrality is closely related to PageRank. More in detail, we show that replacing only one axiom, called Lack of Self-Impact, with another one, called Edge Swap, results in the new axiomatization of PageRank. Finally, we argue that Lack of Self-Impact is desirable in various settings and explain why violating Edge Swap may be beneficial and may contribute to promoting diversity in the centrality measure
Herein we present a novel approach of identifying community structures in complex networks. We propo...
The PageRank algorithm, which has been ``bringing order to the web" for more than twenty yea...
none3noTwo concepts of centrality have been defined in complex networks. The first considers the cen...
Measurement of graph centrality provides us with an indication of the importance or popularity of ea...
Abstract. Many popular measures used in social network analysis, including centrality, are based on ...
Nodes can be ranked according to their relative importance within a network. Ranking algorithms base...
In the study of small and large networks it is customary to perform a simple random walk where the r...
Many scholars have tried to address the identification of critical nodes in complex networks from di...
AbstractA random walk can be used as a centrality measure of a directed graph. However, if the graph...
In this paper, we consider three variations on standard PageRank: Non-backtracking PageRank, $\mu$-P...
We introduce a refined way to diffusely explore complex networks with stochastic resetting where the...
Given a social network, which of its nodes are more central? This question has been asked many times...
Abstract—Is the random walk appropriate for modeling and analyzing social processes? We argue that m...
The role of an actor in a social network is identified through a set of measures called centrality. ...
Identifying the influential nodes in complex networks is a fundamental and practical topic at the mo...
Herein we present a novel approach of identifying community structures in complex networks. We propo...
The PageRank algorithm, which has been ``bringing order to the web" for more than twenty yea...
none3noTwo concepts of centrality have been defined in complex networks. The first considers the cen...
Measurement of graph centrality provides us with an indication of the importance or popularity of ea...
Abstract. Many popular measures used in social network analysis, including centrality, are based on ...
Nodes can be ranked according to their relative importance within a network. Ranking algorithms base...
In the study of small and large networks it is customary to perform a simple random walk where the r...
Many scholars have tried to address the identification of critical nodes in complex networks from di...
AbstractA random walk can be used as a centrality measure of a directed graph. However, if the graph...
In this paper, we consider three variations on standard PageRank: Non-backtracking PageRank, $\mu$-P...
We introduce a refined way to diffusely explore complex networks with stochastic resetting where the...
Given a social network, which of its nodes are more central? This question has been asked many times...
Abstract—Is the random walk appropriate for modeling and analyzing social processes? We argue that m...
The role of an actor in a social network is identified through a set of measures called centrality. ...
Identifying the influential nodes in complex networks is a fundamental and practical topic at the mo...
Herein we present a novel approach of identifying community structures in complex networks. We propo...
The PageRank algorithm, which has been ``bringing order to the web" for more than twenty yea...
none3noTwo concepts of centrality have been defined in complex networks. The first considers the cen...