Social Network Analysis in Python. A practical example of Social Network Analysis of Game of Thrones using NetworkX
This is a quick tutorial about Social Network Analysis using Networkx taking as examples the characters of Game of Thrones. We got the data from the GitHub merging all the 5 books and ignoring the “weight” attribute.
With Network Science we can approach many problems. Almost everything could be translated to a “Network” with Nodes and Edges. For example, Google Maps is a network where the Nodes could be the “Places” and Edges can be the “Streets”. Of course, the most famous network is *Facebook *which is an “undirected” graph, and the *Instagram *which is “directed” since we have the people that we follow and our followers. The nodes are the “users” and the “edges” are the connections between them. Notice that both “nodes” and “edges” can have attributes. For example, node attributes in Facebook can be the “Gender”, “Location”, “Age” etc and edge attribute can be “date of the last conversation between two nodes”, ‘number of likes”, “date they connected” etc.
Notice that with Network Analysis we can apply recommendation systems but this is out of the scope of this tutorial.
Social Network Analysis of Game of Thrones in Python. A practical example of Social Network Analysis of Game of Thrones using NetworkX.
We will be working on the "Game of Thrones" dataset that will help us to analyze different characters and battles in the game. We will also be doing analysis using Python libraries such as Pandas and Seaborn
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