The SRF challenge, where a new news-layout should be proposed, inspired us to think about how a new article-layout could be rated. So we went one step back and had a look at studies that describe how users read, based on eye-tracking. As eye-tracking is cumbersome and only possible in specialized studies, not as much data is available. So we thought about a new way to track what a user reads and how to evaluate if the important information in an article reaches the audience.

What it does

Articulator tracks which sentences the user reads on mobile-phones without the need of a camera or eye-tracking device. Admin users are then able to get a heatmap-like visualization of their article, to see what users have read or which part is looked at the most.

How we built it

We used Javascript to track the users behaviour and persist that on a python-backend, which then delivers the data to visualize it an admin web-app.

Challenges we ran into

Tracking without knowing where the user is looking is hard and the visualization of it is also cumbersome.

Accomplishments that we're proud of

We were astonished by how well it worked, as we were not sure at the beginning, if that concept could even work.

What we learned

Sometimes things can be easier than they look.

What's next for Articulator

Not sure yet :-)

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