Social network visualization for the co-authorship network using the data provided. The data consist of a single column in the following format: Ghasemaghaei, Maryam; Ebrahimi, Sepideh; Hassanein, Khaled Calculate the following using inbuilt Python (or R) functions: d. What’s the clustering coefficient of this network? What does the clustering coefficient of a network show? e. What’s the transitivity of this network? What does the transitivity of a network
Social network visualization for the co-authorship network using the data
provided.
The data consist of a single column in the following format:
Ghasemaghaei, Maryam; Ebrahimi, Sepideh; Hassanein, Khaled
Calculate the following using inbuilt Python (or R) functions:
d. What’s the clustering coefficient of this network? What does the clustering
coefficient of a network show?
e. What’s the transitivity of this network? What does the transitivity of a network
show?
f. What’s the diameter of this network?
g. Which node has the highest degree centrality? What is the significance of this
centrality measure for the co-authorship network?
h. Which node has the highest closeness centrality? What is the significance of this
centrality measure for the co-authorship network?
i. Which node has the highest betweenness centrality? What is the significance of this
centrality measure for the co-authorship network?
j. Do you observe any clusters or subgraphs in this network? If yes, what may be the
underlying reason(s) behind the formation of such clusters or subgraphs?
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