Working with Social Graphs w/ Python

Data Science Experiment 2

Heroic_Social_Network_Tinkering.py is Work in Progress

Began with Social_Graphing_BabySteps.py to experiment with graphing social networks.

Project Goals:

1. Importing, Preparing, Exploring Social Networks in Python

2. Finding strong ties between individuals in a social network

3. Finding key (or central) individuals in a social network

4. Explore characteristics of entire social networks

5. Clustering and community detection in social networks using Centrality Algorithms

6. Visualizing Social Graphs

Toolkit + Credits

Practical Data Science Cookbook: 89 hands-on recipes to help you complete real-world data science projects in R and Python by Tony Ojeda, Sean Patrick Murphy, Benjamin Bengfort and Abhijit Dasgupta. This is an excellent resource for beginning in the world of Data Science with R and Python and I am very thankful to these guys for putting together a fantastic book!

1. NetworkX - Well-maintained Python library for the creation, manipulation, and study of the structure of complex networks.

2. matplotlib - A Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms.

3. python-louvain - Small Python library built solely for the purpose of using the Louvain method for community detection.