Jonathan Harris and Sepandar Kamvar have created We Feel Fine, a tool (it doubles as an art project) that analyzes and parses the emotional content of blog posts. We Feel Find is a simple Java applet that runs in the browser. It scours RSS feeds and seeks out posts that contain the word "feel." The tool presents the writings in six different ways, or movements.
The Madness movement, shown above, is quite chaotic — it gives the impression of a kinetic, emotional tag cloud. The movement called Murmurs simply lists random statements about how people are feeling. The Mobs movement ranks emotions based on their popularity.
Each of the six movements provides geographic and demographic information about the author of each snippet. In most cases, you are able to see where the person is, their age, whether they are male or female and what the weather was like when they wrote their emotional statement. Each movement gives you the opportunity to drill down into the data set and explore specific feelings or demographics. If you play with the tool and interact with the data, you'll begin to get a feel for how it works.
My favorite of the six movements is Montages. The movement shows photos along with some accompanying text. Since the images and text snippets are presented totally out of context, the resulting juxtapositions can produce moments of unexpected beauty.
It's one of the many places within We Feel Fine where the meaning of the content itself is changed by the presentation. We Feel Fine is also a remarkable statement about humans use technology to express their emotions. The content gathered by the tool is candid and revealing, even though it is presented in a way that maintains a certain level of anonymity. It's a testament to the confessional nature of our "look at me" culture.
[thanks to Elizabeth M. for the link!]
