Exercise for Chapter 6: Centrality
Exercise 1
(a) Calculate
Degree
centrality scores of each node in the network above, and complete the
table below.
Degree Centrality
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(b) Calculate
Closeness
centrality scores of each node in the network above, and complete the
table below. (Do not forget to take inverse.)
Closeness Centrality
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Score |
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(c) Calculate
Betweenness
centrality scores of each node in the network above, and complete the
table below.
Betweenness Centrality
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Score |
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(d) Suppose the above
network refers to friendship network. Each node represents a person,
and each edge represents friendship between the persons at ends.
If you are interested in finding the most poplar person in the network,
which centrality measure is the most appropriate? Give the answer
with reasons why it is the most appropriate.
(e) Suppose the above
network refers to information flow network of an organization. Each
node represents a section in the organization, and each edge represents
a possible information exchange between the sections at ends. If
you are interested in finding the section that can most efficiently
obtain information from every other section, which centrality measure
is the most appropriate? Give the answer with reasons why it is the
most appropriate.
(f) Again, suppose
the above network refers to information flow network of an organization.
If you are interested in finding the section that can most frequently
control information flow in the network, which centrality measure is
the most appropriate? Give the answer with reasons why it is the
most appropriate.
Exercise 2
(a) For each Network,
calculate the three centrality indexes (degree, closeness, and betweenness)
for each entire graph (Not for each node of a graph) . Which
graph is more centralized ?
(b) Comparing the centralized
and non-centralized graph above, discuss advantages and disadvantages of
centralized network.
Exercise 3
Centrality can be used
as an index of power in networks, because the most central node is more
likely to occupy the most powerful position. Do you think it is true ?
Answer with reasons why you think so.
If you have questions, ask
Motoki. mwatabe@ucla.edu