In online forums or virtual communities, the interactive relationships among members are similar to actual interpersonal social networks. Each member’s position in the social network affects the individual’s ability to resources for data or organized information. The position of members in networks also considerably affects the degree of opportunity to engage in activities that share individual...

Many Entity Linking systems use collective graph-based methods to disambiguate the entity mentions within a document. Most of them have focused on graph construction and initial weighting of the candidate entities, less attention has been devoted to compare the graph ranking algorithms. In this work, we focus on the graph-based ranking algorithms, therefore we propose to apply five centrality m...

We study the popular centrality measure known as effective conductance or in some circles as information centrality. After reinterpreting this measure in terms of modulus (energy) of families of walks on the network, we introduce a new measure called shell modulus centrality, that relies on the egocentric structure of the graph. Egonetworks are networks formed around a focal node (ego) with a s...

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...

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)...

Recently Boldi and Vigna proposed axioms that would characterize good notions of centrality. We study a random-walk version of closeness centrality and prove that is satisfies Boldi-Vigna axioms for non-directed graphs.

Centrality measures define the relationship between particular structural features of a network. Although network analysis has been utilized to express the most relevant physical, topological and static properties of networks, dynamic and temporal aspects are mostly disregarded. For example, in travel network studies the physical street network is assumed to be static, although it can have rele...

We derive new, exact expressions for network centrality vectors associated with classical Watts-Strogatz style “ring plus shortcut” networks. We also derive easy-to-interpret approximations that are highly accurate in the large network limit. The analysis helps us to understand the role of the Katz parameter and the PageRank parameter, to compare linear system and eigenvalue based centrality me...

Graph centrality has been extensively applied in Social Network Analysis to model the interaction of actors and the information flow inside a graph. In this paper, we investigate the usage of graph centralities in the Shape Matching task. We create a graph-based representation of a shape and describe this graph by using different centrality measures. We build a Naive Bayes classifier whose inpu...

Social Network Analysis (SNA) is an active area of research, not only in inter – disciplinary areas but also in multidisciplinary areas. Key players can be identified using different methodologies, including centrality measures. Few works are done using different datasets in different areas. In this paper, we tried to identify the sets of key players from blog posts ad responses that are posted...