This document provides a beginner's guide to using the igraph library in Python. It discusses what networks are, how to realize and visualize graphs in igraph. It also covers scale-free networks and power laws, using a co-authorship dataset to demonstrate that these networks follow a power law distribution with a few nodes having many connections. Code and a plot obtained are shown as an example of analyzing a scale-free network in igraph.

1. A beginner’s guide to igraph in python
Tapesh Mandal
August 21, 2017
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2. What are networks?
• Networks are a set of vertices or nodes connected by edges.
A set of examples would be :-
A interaction network between users on a social networking site.
A network of hyperlinked web pages that constitute the internet.
Structure of a protein molecule.
igraph provides you with ready made graph data structures and
various algorithms to extract meaningful information from it.
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3. First step : Realizing a graph
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4. Visualizing the graph
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5. Scale free networks and power law
• Power law
P(d) ∼ d−λ
Source: Albert-Laszlo Barabasi, Network Science The Scale-free property
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6. Experiment on dataset
• Example of a scalefree network is the co-authorship network in the field
of research.
To verify this we take a dataset from UCI Network Repository called
”netscience.gml”, which is a coauthorship network of scientists working
on network theory and experiment, as compiled by M. Newman in May
2006.
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7. Experiment code
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8. Plot obtained
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9. THANK YOU
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