Graphing on a Mac

As per usual, Apple makes it just slightly harder to accomplish things that windows and linux do with flying colours.

To get started, this great blog post shows you all the steps required to get NodeXL working on a mac. They include using virtual box or Amazon EC2

This video shows you how to create a micro-instance of Amazon on your Mac:

 

Another great option for those of you who are using Macs, is to look for other programs which can accomplish similar tasks to NodeXL.

One great example is Gephi, an opensource software designed to generate and export lovely looking graphs.

On this page, you can find both the download links and information for installing on Windows, Mac or linux.

This page offers some great intro tutorials for working with Gephi.

I hope you all enjoy!

Big Data | Big Problems | Big Ambitions

Studying or analyzing social networks can be like playing with double edged knives. Because data is so commonly generated and archived, we are left to question the feasibility of the data we are presented with. However, if we can ‘tame the dragon’ of large data sets, the truths they behold could lead to great treasures.

Wikipedia’s page on Big Data is a great place to introduce yourself to this problem.

One tried and tested approach, commonly employed in the social sciences, is to use some good old triangulation. By triangulation I’m referring to the idea that fancy computers and clever code aren’t the only way to understand how networks can work.
Interviews and surveys are just one way someone can extrapolate even more data, perhaps helping clarify something that doesn’t quite make sense in your social network graph or data.

Here is an example. I have been trying to analyze different subreddits on the website Reddit.com. While this seems like an easy enough task for some programmers out there, it isnt always easy to understand how these networks emerge and work. If  i could ask a few redditors for some of their posting information it might help me to formulate better ways to analyze the graphs, formulate data or understand anomalies.

Some questions you might ask:

  • How often do you post?
  • where do you post on?
  • How many different places do you browse/post?
  • How many people do you know on forums?
  • How many strangers have you met on Reddit?
  • Do you comment, post a link or reply mostly?
  • Do you rely on websites/friends/others for information?
  • etc

Questions like these can help understand the more human sides to social networks and graphs. Hopefully, with clever triangulation, the arts and sciences can meet halfway and combine their efforts in helping to understand massive networks that arise within the our social lives.

Social Network Analysis 101

Our lives are embedded within  networks: online and offline – from social networks to networks of work and institutions, networks of family and friends, networks within our bodies…. the list goes on.

Much research tries to utilize these networks in order to better understand how netowrking takes place, what can be deduced by the networks which form, and what relation do they have to our actual lives.

Below are some interesting links to get you started with your own social network analyses!

– First, let me Wikipedia Social Network Analysis, Social Networks, Network Science & Network theory for you!

– Here is an introduction slide show about Social network analysis

-This is the  link for the International Social Network Analysis Organization.  (On the right you can find the latest journals!)

-Lastly, Here is a link to NodeXL’s gallery of graphs, where you can see some crazy social graphs currently being created!