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MIT’s Immersion shows what can be found through email metadata

I took a quick look at Immersion, a project at MIT by Daniel Smilkov, Deepak Jagdish, and César Hidalgo, that analyzes email metadata from Gmail and builds a fairly interesting social network graph from it.

What is Immersion? via mit.edu

It has been almost two decades since the beginning of the web. This means that the web is no longer just a technology of the present, but also, a record of our past.

Email, one of the original forms of social media, is even older than the web and contains a detailed description of our personal and professional history.

Immersion is an invitation to dive into the history of your email life in a platform that offers you the safety of knowing that you can always delete your data.

Just like a cubist painting, Immersion presents users with a number of different perspectives of their email data.

  • It provides a tool for self-reflection at a time where the zeitgeist is one of self-promotion.
  • It provides an artistic representation that exists only in the presence of the visitor.
  • It helps explore privacy by showing users data that they have already shared with others.
  • Finally, it presents users wanting to be more strategic with their professional interactions, with a map to plan more effectively who they connect with.

So Immersion is not about one thing. It’s about four. It’s about self-reflection, art, privacy and strategy. It’s about providing users with a number of different perspectives by leveraging on the fact that the web, and emails, are now an important part of our past.

I loaded my gmail account, and got a fairly startling rendition of my social network, based on 120,296 emails from 1,968 collaborators (just the ones I didn’t delete).

The tool provides a timeline slider, so you can set the time range to as short as the past few days, everything since 2 January 2006 (when I started using Gmail), or any other fragment.

Screenshot on 2013-07-10 at 14.00.25

I selected David Card, who is the center of the GigaOM cluster of my network. You can click on anyone and see who they are most connected to, and (not shown) there are lists of your top collaborators. Supplemental information is shown when clicking on a specific individual, here David Card:

david card

 

 

This is a simple graph analysis, but it manages to find clusters and weight the degree of my affiliation with people really well.

Just imagine what the NSA can determine by cross analyzing groups of people’s networks. It’s fairly obvious that analyzing metadata is like a blinding searchlight in the social dark matter that lies within our inboxes.