Social Network Analysis: From Graph Theory to Applications with Python

Social network analysis is the process of investigating social structures through the use of networks and graph theory. This article introduces data scientists to the theory of social networks, with a short introduction to graph theory and information spread. It dives into Python code with NetworkX constructing and implying social networks from real datasets. We'll start with a brief intro in network's basic components: nodes and edges. Nodes (A,B,C,D,E in the example) are usually representing entities in the network, and can hold self-properties (such as weight, size, position and any other attribute) and network-based properties (such as Degree- number of neighbours or Cluster- a connected component the node belongs to etc.).