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Social networks are not new, even though websites like Facebook and Twitter might make you want to believe they are; and trust me- I’m not talking about Myspace! Social networks are extremely interesting models for human behavior, whose study dates back to the early twentieth century. However, because of those websites, data scientists have access to much more data than the anthropologists who studied the networks of tribes!

Because networks take a relationship-centered view of the world, the data structures that we will analyze model real world behaviors and community. Through a suite of algorithms derived from mathematical Graph theory we are able to compute and predict behavior of individuals and communities through these types of analyses. Clearly this has a number of practical applications from recommendation to law enforcement to election prediction, and more.

Tribe is a utility that will allow you to extract a network (a graph) from a communication network that we all use often - our email. Tribe is designed to read an email mbox (a native format for email in Python)and write the resulting graph to a GraphML file on disk. This utility is generally used for District Data Labs’ Graph Analytics with Python and NetworkX course, but can be used for anyone interested in studying networks.

For more, please see the full documentation at: http://ddl-tribe.readthedocs.org/en/latest/

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Release files for tribe 1.3

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tribe-1.3-py2.py3-none-any.whl Python 2, Python 3 none any Details

Total release size: 1.3 MB

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