Question

Describe the matrices and formulae used to determine centralization or distribution of data. In the absence of subjective reasoning, would the matrices and formulae lead to a rational decision? Why or why not?

Develop all of the distribution matrices and subjective reasoning for/against distribution, for the problem chosen in Unit 3 (from Appendix). Develop recommendations and explain your reasoning for each choice

Answer 1

step by step explanation:

The idea of centrality of individuals and organization in their social networks was one of the earliest to be pursed by social network analysts.The immediate origins of the idea are to be found in the sociometric concept of the "star"-the person who is the most "popular" in his or her group or who stands at the centre of attention.The formal properties of centrality were intially investigated by Bavelas(1950),and since his pioneering work,a number of computing concepts of centrality have been proposed.As a result of this proliferation of formal measures of centrality,there is considerable confusion in the area.what unites the majority of the approaches to centrality is a concern for the relative centrality of the various points in the graph the question of so-called "point centrality".But from this common concern they diverge sharply.A number of measures of point centrality,focusing on the important distinction between "local" and "global" point centrality.A point in locally central if it has a large number of connections with the other points in its immediate environment.A point is globally central,on the other hand,when it has a position of strategic significance in the overall structure of the network.

Related measurement of point centrality is the idea of the overall"centralization" of a graph, and these ideas have sometimes been confused by the use of the same term to describe them both.

centrality:Local and Global

The concept of point centrality,I have argued,originated in the sociametric concept of "star"".A central point was one which was "at the centre"of a number of connections,a point with a great many direct contacts with other points.The simplest and most straightforward way to measure point of centrality,therefore,is by the degree of various points in the graph.The degree it will be recalled,is simply,the number of other points to which a point is adjancent. A point is central,then if it has a high degree; the corresponding agent is central in the sense of being "well connected".A degree-based measure of point centrality, therefore,the corresponds to the intuitive notion of how well connected a point is within its local environment.Because this is calculated simply in terms of the number of points to which a particular point is adjancent, ignoring any indirect connections,if may have, the degree can be regarded as a measure of local centrality.