Network Science for Fun and Profit

*
Accepted Session
Long Form
Intermediate
Scheduled: Wednesday, June 25, 2014 from 10:00 – 11:45am in B304

Excerpt

Understanding the relationships between data elements has become increasingly valuable, as LinkedIn, Facebook and Google illustrate. Network science provides a means to understand, explain, predict and otherwise utilize these relationships. I will provide a brief overview of network science, with examples and illustrations using R, focused on providing an entry point to their use for fun and profit.

Description

Understanding the relationships between data elements has become increasingly valuable, as LinkedIn’s Economic Graph, Facebook’s Social Graph and Google PageRank illustrate. Network science provides a means to understand, explain, predict and otherwise utilize these relationships. I will provide a brief overview of network science, with examples and illustrations using R, focused on providing an entry point to their use for fun and profit.

Topics will include a bit of historical context and basic terminology, followed by a review of network types, features and statistics, and conclude with examples of their application. Code and data samples will be provided as a starting point for further experimentation and application.

The slides and R presentation source are available for your reference.

Tags

network science, graph analysis

Speaking experience

* I presented "Machine Learning in the Open" at OSB 2012 and "Data Science in the Open" at OSB 2011.
* I have presented at professional conferences (at CMU, ANU, and Stanford).
* I regularly give presentations in the workplace and at Meetup groups.

Speaker

  • Johntaylor

    John Taylor

    iovation

    Biography

    John L. Taylor works as a Senior Data Scientist at iovation, specializing in the application of data mining and machine learning methods to various explanatory and predictive problems. Formerly, he was a graduate student in Logic and Computation at CMU and has BAs in philosophy and psychology.

    John is, in no particular order and among other things, an aspiring polymath, intellectual magpie, cultural gadfly, father and husband, data geek, Brazilian jiu-jitsu hobbyist, bibliophile, pop cultural glutton, recreational mathematician, and skeptic.

    Sessions

      • Title: Network Science for Fun and Profit
      • Track: Cooking
      • Room: B304
      • Time: 10:0011:45am
      • Excerpt:

        Understanding the relationships between data elements has become increasingly valuable, as LinkedIn, Facebook and Google illustrate. Network science provides a means to understand, explain, predict and otherwise utilize these relationships. I will provide a brief overview of network science, with examples and illustrations using R, focused on providing an entry point to their use for fun and profit.

      • Speakers: John Taylor