Social Network Analysis

SOCIAL NETWORK ANALYSIS
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Question Two
* a screenshot of the “Overall Metrics” of the social network
Explanation:
Most of the metrics are mapped to the various aspects of a network structure. For instance, a vertex that represents a user in a network can also be managed such that it presents all other users who follow the parent user. Centralities such as betweenness and degree are used in the identification of the most influential node in a group. Besides, centrality is defined as the measure of the importance and relevance of a node in a network. Other centralities include closeness, Eigenvector centrality, which describes how well nodes are connected in a network. From the above graph, most of these metrics are analyzed such that metrics with higher values indicate a high level of relevance and resonance.
* a screenshot of the “Groups” metrics for companies and politicians
Explanation:
There are two groups: politicians and companies. Politicians have a high number of vertices as well as edges connected. This indicates that politicians have more nodes connected as compared to companies. Also, politicians have higher graph density
* a screenshot of the graph pane (in Document Actions) with labeled and colored nodes
Explanation:
The coloring of the edges is based on the size of values for each edge. This also determines the width and the opacity, and transparency of the edges. Also, the labeling and sizes of the vertices depend on the values of the followers.
Question Three
The graph density of a particular network refers to the number of available edges over the number of possible edges in the network graph. The density of the network obtained from the graph above is “0.059772448”. The set of the data ...