In this paper, we propose a method for rapid computation of group betweenness centrality whose running time (after preprocessing) does not depend on network size. The calculation of group betweenness centrality is computationally demanding and, therefore, it is not suitable for applications that compute the centrality of many groups in order to identify new properties. Our method is based on th...

A manufacturing industry contributes around 10% Malaysian economy. It provides economic opportunities for related industries and business. However, the number of accidents in manufacturing sector, including fatal accidents, has been increased from time to time. To understand the real situation, in this paper, we used a correlation network analysis to analyze 43 characteristics of worker’s behav...

Measuring the importance of nodes in a network with centrality measure is core task any application. There are many measures available and it speculated that encode similar information. We give an explicit non-linear relationship between two most popular node centrality: degree closeness. Based on shortest-path tree approximation, we analytic derivation shows inverse closeness linearly dependen...

BACKGROUND Living systems are associated with Social networks - networks made up of nodes, some of which may be more important in various aspects as compared to others. While different quantitative measures labeled as "centralities" have previously been used in the network analysis community to find out influential nodes in a network, it is debatable how valid the centrality measures actually a...

In this paper, we measure and analyze the correlation of betweenness centrality (BWC) to five centrality measures, including eigenvector centrality (EVC), degree centrality (DEG), clustering coefficient centrality (CCC), farness centrality (FRC), and closeness centrality (CLC). We simulate the evolution of random networks and small-world networks to test the correlation between BWC and the five...

This paper introduces a new centrality measure, nominated by the authors as mobility centrality (C), which arose during the study of the interregional road network in Greece. The proposed measure is constructed by the use of the anagogic method considering the formula of the kinetic energy of a particle in Physics and adjusting its mathematical analogue to the case of the interregional road net...

In this study, we develop a theoretical model based on social network theories and analytical methods for exploring collaboration (co-authorship) networks of scholars. We use measures from social network analysis (SNA) (i.e., normalized degree centrality, normalized closeness centrality, normalized betweenness centrality, normalized eigenvector centrality, average ties strength, and efficiency)...

INTRODUCTION Use of online social networks for smoking cessation has been associated with abstinence. Little is known about the mechanisms through which the formation of social ties in an online network may influence smoking behavior. Using dynamic social network analysis, we investigated how temporal changes of an individual's number of social network ties are prospectively related to abstinen...

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...