Sentence examples for many centrality from inspiring English sources

For unweighted networks where edges are just present or absent and have no weight attached, many centrality measures have been presented, such as degree, betweenness, closeness, eigenvector and subgraph centrality.

Many centrality measures have been proposed yet; the most famous ones are degree centrality, closeness centrality, eccentricity and betweenness centrality (Hanneman and Riddle 2005).

There are many centrality statistics, each tapping a different aspect of social structure, when combined with decisions about actors and which relations to code, this creates a versatile tool kit through which to understand group structure.

We obtained as many centrality measurements as possible to explore the properties of LWDH genes.

Therefore, many centrality methods have been come up with such as Degree Centrality (DC) [ 6], Betweenness Centrality (BC) [ 7], Closeness Centrality (CC) [ 8], Subgraph Centrality (SC) [ 9], Eigenvector Centrality (EC) [ 10], Information Centrality (IC) [ 11], Edge Clustering Coefficient Centrality (NC) [ 12] and so on.

For many, the centrality of Anglo-Saxon traditions of freedom and even capitalism was diminished in an effort to secure racial solidarity in an increasingly complex and decentralized world.

Though many different centrality metrics exist in social network analysis (each capturing different aspects of social position or organization within a connected social group [13], [14], [16]), we chose three basic, traditional centrality measures broadly used in the field of social network theory.

Since the 1950s, along with some global topological indices, many vertex centrality indices were introduced.

In order to not overemphasize one particular – out of the many – dimensions of centrality in networks, we chose to use complementary centrality measures that capture different aspects of importance at the same time.

In social science, many measures including centrality [17], complement [14], and reciprocal [5] were developed to describe system properties.

It was previously shown that the diversity graphs are highly centralized consisting of many nodes of low centrality and a few nodes of high centrality.