This study proposes a different angle to social network analysis that evaluates patent value and explores its influencing factors using the network centrality and network position. This study utilizes a logistic regression model to explore the relationships in the LED industry between patent value and network centrality as measured from out-degree centrality, in-degree centrality, in-closeness ...

The task of identifying the main key nodes in the dark (covert) networks is very important for the researchers in the field of dark networks analysis. This analysis leads to locate the major nodes in the network as the functionality can be minimized by disrupting major key nodes in the network. In this paper, we have primarily focused on two basic network analysis metrics, degree and betweennes...

The author conducts an extensive correlation coefficient analysis of four prominent centrality measures for mobile ad hoc networks. The centrality measures considered are the degree-based degree centrality and eigenvector centrality, and the shortest path-based betweenness centrality and closeness centrality. The author evaluates the correlation coefficient between any two of the above four cen...

Users are not often aware of privacy risks and disclose information in online social networks. They do not consider the audience that will have access to it or the risk that the information continues to spread and may reach an unexpected audience. Moreover, not all users have the same perception of risk. To overcome these issues, we propose a Privacy Risk Score (PRS) that: (1) estimates the rea...

We investigated the reliability of nodal network metrics of functional connectivity (FC) networks of magnetoencephalography (MEG) covering the whole brain at the sensor level in the eyes-closed (EC) and eyes-open (EO) resting states. Mutual information (MI) was employed as a measure of FC between sensors in theta, alpha, beta, and gamma frequency bands of MEG signals. MI matrices were assessed ...

Centrality metrics evaluate paths between all possible pairwise combinations of sites on a landscape to rank the contribution of each site to facilitating ecological flows across the network of sites. Computational advances now allow application of centrality metrics to landscapes represented as continuous gradients of habitat quality. This avoids the binary classification of landscapes into pa...

The relationships among the members of a population can be visualized using individual networks, where each individual is a node connected to each other by means of links describing the interactions. The centrality of a given node captures its importance within the network. We hypothesize that in mutualistic networks, the centrality of a node should benefit its fitness. We test this idea studyi...

Abstract Time-varying graphs (TVGs) enable the study and understanding of dynamics many real-world networked systems. The notion centrality in TVG scenarios generally refers to metrics that assess relative importance nodes over time evolution a complex dynamic network. In contrast, Time Centrality, which evaluates instants networks, is still little explored. Indeed, few works on Centrality base...