NikosVlachakis / Social_Network_Analysis

Laboratories for the course "Social Network Analysis" at ECE-NTUA, in 2022.

Social Network Analysis - 9th semester course at National Technical University of Athens

Lab 1: Complex Network Types and Metrics

In this lab, you will learn about the construction and visualization of complex network types, as well as the calculation of important network metrics. Specifically, you will learn about:

1. The construction and visualization of complex network types
2. The calculation of network metrics such as clustering coefficient, minimum path length, and node eccentricity (diameter, radius, circumference, and center)
3. The calculation of node centrality metrics such as degree centrality, closeness, betweenness, Katz centrality, and the application of PageRank to a real network (using the web-Stanford.txt file)
4. The study of connectivity and robustness of networks
5. The study of evolutionary network transformation
6. The study of real networks

Lab 2: Social Structure Analysis in Artificial and Real Complex Network Topologies

In this lab, you will study the Social Structure Analysis in Artificial and Real Complex Network Topologies. You will be asked to:

1. Find and show the node degree distribution and the average degree of each topology
2. Find and show the distribution of node clustering coefficient and the average clustering coefficient of each topology
3. Find and show the distribution of proximity centrality and the average proximity centrality of each topology

The data of the real networks you will use can be downloaded from the following links:

Lab 3: Link Prediction with Similarities dataset (DBpedia)

In this lab, you will make use of the Similarities dataset (DBpedia) to learn about link prediction. You will learn about:

1. Graph construction and preprocessing for link prediction
2. Introduction to similarity-based metrics for link prediction
3. Link prediction based on similarity-based metrics
4. Link prediction with embedding based on Random Walks