I just finished this little web app. It uses the same word-association dataset I’ve been obsessed with for the past year. Enter words, and it will produce an image showing the connections between your input and other connected words.
Here is some sample input from actual users:
In an effort to get at the essence of font-design, I averaged all the fonts on my computer and got this:
All the fonts on my computer [image].
I did it in Flash. Originally I was going to use Processing, but its font handling is clunky. (Flash, I later discovered, has its own rendering issues. Next time I’ll try Open Frameworks). Here are two embedded apps that average web-safe fonts:
Sans-serif fonts [flash] Serif fonts [flash]
And here’s the source code:
I added some features to my Paths App. It’s based on a word association database from the University of South Florida. Starting in 1973 they gave word association tests to 6,000 people resulting in a database with almost 750,000 entries. The results are available online but only as text files. I’m working to visualize the data.
Related: Association Apps
Six months ago I became obsessed with a project at the University of South Florida. In 1973 the psychology department began performing word association tests. A word association test is where you say the first thing that comes to mind when given a word. For example, if I gave you “Cat” you might say “Dog.” Over 25 years USF performed around 750,000 of these tests on almost 6,000 individuals. The results are online here. In their current form the results are hard-to-read text files, so I wrote programs that could slice and dice the data and produce readable output. Eventually, I hope to find an algorithmic definition of repression. In the meantime, here are some of the apps I made.
SEMANTIC WEB VISUALIZER
Enter words separated by commas, press go, and get an image showing the connections between your input and other connected words.
COMPARE
Compares each word in the database with respect to two words you enter. Enter “Picasso” and “Mona Lisa” and you will receive a list of words that are closer to Picasso (”abstract”), closer to Mona Lisa (”portriait”), and equidistant (”painting”).
PATHS
This app shows what words are most closely associated with the word you enter. Rolling over the words will show you the associative leaps required to get to your word.
LOCAL CENTER
Type in a series of words separated by commas, and see the results most closely associated with that series. For example, if you enter “fangs, blood, coffin” you are shown “Vampire, Dracula,” and so on.
HIGHLIGHT
This app lists words closest to your “list-order word.” It will then change the size of the results according to a “magnifying word.” For example, one looking for evidence of an oedipal complex might enter “mother” and “sex.” Words will be listed in order of their association with “mother.” Words more closely associated with “sex” will appear larger than those less associated.
HIGHLIGHT NEGATIVE
This is very similar to HIGHLIGHT, except font size is changed according to distance from a group of “unpleasant” words [links to pdf]. As a result words are magnified according to their “unpleasantness.”
CHARLIE KAUFMAN INSPIRATION MACHINE
I noticed that words not directly related to an input word, yet still somewhat related, started to resemble elements of a Charlie Kaufman screenplay. This app lists elements that are 1 degree away from an input word. Enter “murder” and you get “accident, bear, tomahawk, drugs, television”–all you need to start your screenplay.
[Update]
For those of you who want to mess around with this, here is the study’s data as a a sql database.