Most emerging infectious diseases (EIDs) in humans have arisen from animals. Identifying high-risk hosts is therefore vital for the control and surveillance of these diseases. Viewing hosts as connected through the parasites they share, we use network tools to investigate predictors of parasitism and sources of future EIDs. We generated host-parasite networks that link hosts when they share a p...

Centrality metrics have been used in various networks, such as communication, social, biological, geographic, or contact networks. In particular, they order to study and analyze targeted attack behaviors investigated their effect on network resilience. Although a rich volume of centrality has developed for decades, limited set commonly use. This paper aims introduce existing discuss applicabili...

The theoretical foundations for a definition of distance on ontologies are laid out in this paper. The distance measure is defined using the well known concepts of entropy and mutual information from information theory. These formal methods are adapted for practical use in ontologies through the definition of useful discrete random variables. These include centrality measures like degree, close...

We perform social network analysis on 53 students split over three semesters and 13 groups, using conventional measures like eigenvector centrality, betweeness centrality, and degree centrality, as well as defining a variant of the Abelian Sandpile Model (ASM) with the intention of modeling stress propagation in the college classroom. We correlate the results of these analyses with group projec...

The calculation of centrality measures is common practice in the study of networks, as they attempt to quantify the importance of individual vertices, edges, or other components. Different centralities attempt to measure importance in different ways. In this paper, we examine a conjecture posed by E. Estrada regarding the ability of several measures to distinguish the vertices of networks. Estr...

The ever increasing body of social networks creates an opportunity for extensive network analysis and investigations of communications, cliques, and network contributions. In this study, we focus our attention on the Enron email corpus and the corresponding network of employees, attempting to gather information from the email communications. Methods of data reduction on the email corpus were us...

Opportunistic networks utilize pocket switching for routing where each node forwards its messages to a suitable next node. The selection of the forwarder is crucial efficient performance protocol. In any opportunistic network, some nodes have paramount role in process and these could be identified with assistance existing centrality measures available network theory. However, central tend suffe...

The central vertices in complex networks are of particular interest because they might play the role of organizational hubs. Here, we consider three different geometric centrality measures, excentricity, status, and centroid value, that were originally used in the context of resource placement problems. We show that these quantities lead to useful descriptions of the centers of biological netwo...

How to identify influential nodes in social networks is of theoretical significance, which relates to how to prevent epidemic spreading or cascading failure, how to accelerate information diffusion, and so on. In this Letter, we make an attempt to find effective multiple spreaders in complex networks by generalizing the idea of the coloring problem in graph theory to complex networks. In our me...