Recent developments in network theory have allowed for the study of the structure and function of the human brain in terms of a network of interconnected components. Among the many nodes that form a network, some play a crucial role and are said to be central within the network structure. Central nodes may be identified via centrality metrics, with degree, betweenness, and eigenvector centralit...

Network data is usually not error-free, and the absence of some nodes is a very common type of measurement error. Studies have shown that the reliability of centrality measures is severely affected by missing nodes. This paper investigates the reliability of centrality measures when missing nodes are likely to belong to the same community. We study the behavior of five commonly used centrality ...

We present a modified Deffuant-Weisbuch opinion dynamics model that integrates the influence of media campaigns on opinion. Media campaigns promote messages intended to inform and influence the opinions of the targeted audiences through factual and emotional appeals. Media campaigns take many forms: brand-specific advertisements, promotions, and sponsorships, political, religious, or social mes...

In this paper, the relationship between the network synchronizability and the edge distribution of its associated graph is investigated. First, it is shown that adding one edge to a cycle definitely decreases the network sychronizability. Then, since sometimes the synchronizability can be enhanced by changing the network structure, the question of whether the networks with more edges are easier...

The betweenness and closeness metrics are widely used metrics in many network analysis applications. Yet, they are expensive to compute. For that reason, making the betweenness and closeness centrality computations faster is an important and well-studied problem. In this work, we propose the framework BADIOS which manipulates the graph by compressing it and splitting into pieces so that the cen...

We study the lobby index ( l for short) as a local node centrality measure for complex networks. The l is compared with degree (a local measure), betweenness and Eigenvector centralities (two global measures) in the case of a biological network (Yeast interaction protein-protein network) and a linguistic network (Moby Thesaurus II ). In both networks, the l has poor correlation with betweenness...