Centrality indices aim to quantify the importance of nodes or edges in a network. A number of new centrality indices have recently been proposed to try and capture the role of nodes in connecting the network. While these indices seem to deliver new insights, to date not enough is known about their theoretical properties. To address this issue, we propose an axiomatic approach. Specifically, we ...

Incorporating skills in reinforcement learning methods results in accelerate agents learning performance. The key problem of automatic skill discovery is to find subgoal states and create skills to reach them. Among the proposed algorithms, those based on graph centrality measures have achieved precise results. In this paper we propose a new graph centrality measure for identifying subgoal stat...

Many studies on coauthorship networks focus on network topology and network statistical mechanics. This article takes a different approach by studying micro-level network properties, with the aim to apply centrality measures to impact analysis. Using coauthorship data from 16 journals in the field of library and information science (LIS) with a time span of twenty years (1988-2007), we construc...

We consider a broad class of walk-based, parameterized node centrality measures for network analysis. These measures are expressed in terms of functions of the adjacency matrix and generalize various well-known centrality indices, including Katz and subgraph centrality. We show that the parameter can be “tuned” to interpolate between degree and eigenvector centrality, which appear as limiting c...

We study the causal impact of network centrality on educational outcomes using field experiments in primary schools in Bangladesh. After obtaining information on friendship networks, we randomly allocate students into groups and give them individual and group assignments. We find that groups that perform best are those whose members have high Katz-Bonacich and key-player centralities. Leaders a...

Centrality is an important concept in the study of social networks, which in turn are important in studying organisational and team behaviour. For example, “central” individuals influence information flow and decisionmaking within a group. However, the relationship between mathematical measures of centrality on the one hand, and the real-world phenomenon of centrality on the other, is somewhat ...

We deliver a short overview of different centrality measures and influence concepts in social networks, and present the relation-algebraic approach to the concepts of power and influence. First, we briefly discuss four kinds of measures of centrality: the ones based on degree, closeness, betweenness, and the eigenvector-related measures. We consider centrality of a node and of a network. Moreov...

Centrality is an important concept in the study of social networks, which in turn are important in studying organisational and team behaviour. For example, “central” individuals influence information flow and decisionmaking within a group. However, the relationship between mathematical measures of centrality on the one hand, and the real-world phenomenon of centrality on the other, is somewhat ...