Here you can see that the most popular tag in our pool is ‘glocalproject’. The size of the tags then descend with their popularity. If you look at the largest size of the first image (4000px x 2000px!) you can read a lot of the tags.

For the record, the longest tag in our pool is ‘hesquitecontainedandlikestoprancearoundwithmeatcollege’, which, not surprisingly, only appears once.

Stay tuned for more!

One of the things that we are looking at in this project are the myriad relationships between images. Some of these relationships are clear – photos taken by the same artist, images from the same town, or with a shared tag. Other relationships are hidden a bit deeper. Over the last few weeks, I’ve been working with software (Processing, Flash, PHP, C++) to make some tools that can help us explore these unseen links. Here are some early sketches from this work – showing some ways the links and pathways within the Glocal Pool can be explored:

flickr.com/photos/blprnt/sets/72157606955337736/

If you look hard enough, you may be able to see your own images in the networks! With 1,200+ images, I had to pick some photos at random to be the ’seed’. Hopefully soon you’ll be able to try this out with your own images. This is a similarity map, with a fairly high tolerance. The ring around the center image is made up of the images that are most similar to the seed. From those images, the offshoots represent more similarity chains. The farther you get from the center, the less similar the images are to the seed:

 Here’s the same map with a lower tolerance:

 This is a colour map, showing images with similar overall colour to the central image:

 And one more: 

You can see the full photoset here.