Resources:
Graph mining - lesson 1: Introduction to graphs and networks
http://www.nathalievialaneix.eu/teaching/m2se/M2SE-network_1.pdf
Erdős–Rényi model
https://en.wikipedia.org/wiki/Erd%C5%91s%E2%80%93R%C3%A9nyi_model
Random Graphs
https://en.wikipedia.org/wiki/Random_graph
Examples of small-world networks
https://en.wikipedia.org/wiki/Small-world_network#Examples_of_small-world_networks
Case Study: Small World Phenomenon
https://introcs.cs.princeton.edu/java/45graph/
Random Graphs: Model of Social Networks
http://www.pnas.org/content/99/suppl_1/2566
Power Law Distribution
https://en.wikipedia.org/wiki/Power_law#Power-law_probability_distributions
Poisson distribution
https://en.wikipedia.org/wiki/Poisson_distribution
Watts–Strogatz model
https://en.wikipedia.org/wiki/Watts%E2%80%93Strogatz_model
Dirac delta function
Everywhere it is zero except at zero
https://en.wikipedia.org/wiki/Dirac_delta_function
Barabási–Albert (BA):
https://en.wikipedia.org/wiki/Barab%C3%A1si%E2%80%93Albert_model#Degree_distribution
Random Graph Generators in Python Libraries
https://networkx.github.io/documentation/networkx-1.10/reference/generators.html
Random Graph Generators in R Libraries
https://rpubs.com/lgadar/generate-graphs