I found really fascinating this eyetracking heatmap form one of the latest Jakob Nielsen's Alertbox articles.

The areas where users looked the most are colored red; the yellow areas indicate fewer views, followed by the least-viewed blue areas. Gray areas didn't attract any fixations.

As argued by Nielsen, the dominant reading behavior follows an F shape: a first horizontal movement, a second horizontal movement a bit below, and a vertical scan on the left, and it is quite consistent over several different types of web pages and tasks.

It's incredibly fascinating to see how visualization can help in tracking and then displaying human behaviors in a way that makes emergent patterns readily visible. There is a growing interest and focus on collecting bits of human information and given them a visual counterpart ready for analysis. Other examples have been posted in this blog before.

The key factor of this kind of visualizations is the fact that visualization permits to see the evolution of things summed up in aggregate visual information. Frequency is often the key parameter that is used to visualize behavior: frequency of road paths, visual glimpses, airplane trajectories, etc. Alternatively, the visualization can be used to replay things at a different rate and thus to expose dynamic behaviors that couldn't be detected at a human pace.

It's a notable fact that replaying things at a different rate permits to see some patterns that would not be apparent otherwise. The image that comes into my mind is the typical video of a flower's entire life replayed in a few minutes (see this wonderful Amaryllis). Or a sequence of pictures taken always from the same position over an extended period of time. A more elaborated idea is Alan's Slow Time: if we could replay our life and use band-pass filters to select things that routinely happen at very low frequencies (e.g., every day, month, year) we could notice interesting recurring patterns of ourselves. Notably, finding your keys!:

Take the home. Band pass in the millihertz range. Start off by removing the things faster than millihertz - to and from movements of people disappear and we are left with the things that change only slowly - rather like a series of long exposure night-time frames, the hurrying people become ghostly mist against the background. Now remove the things that do not change in the millihertz range, things that are the same for hours and days. Watch the resulting images, just the moments of millihertz change - the things put down and picked up, or perhaps put down and never picked up - "that's where I left my keys!"

It would be great to see one day this idea realized in a real prototype.