For this assignment, we were tasked with creating a data visualization that uses two potentially unrelated APIs to create one cohesive “mashup” visualization. Chris Piuggi and I teamed up to make something out of the Facebook API and NYTimes Best Sellers API, but after some initial research quickly changed to the NYTimes Movie Reviews API in order to access information that would be more relevant in the context of a social network service.
We began to develop the idea of a Facebook Movie Recommendation Service (FMRS) that would primarily make use of the Facebook API to pull information about your favorite movies as well as those of your friends to create a sort of visual Pandora for movies. This interaction provided users a path to discover similarities between friends and movies, and begin to discover new titles they might enjoy. The envisionined application seeks to provide recommendations based on friends rather than individual preferences to show a wealth of options, as well as prompt discover between the user and data. The hope would be to grow this into a full fledged system in which users could recommend movies and find ratings, based on their friends, as well as their preferences. Integration of Netflix API could potentially create this dynamic interchange between the user and the data.
Aside from the data being accessed but not passable between languages at our point of progress, we also created a Processing sketch that we included in a web page to perform the actual visualization. In the sketch, the user would click the wheel or hit a key to move the “carousel” either forward or backward in order to see each of their friend’s movie preferences. A video of the interaction can be viewed below.
In the future it would be great to get all the variables talking to each other and really get this visualization off the ground. We think that it would provide a unique and useful service to Facebook users once we integrate the separate movie information and reviews and got the visuals working exactly as we would like them, and hope to see a more developed version in the future now that we’ve been able to learn a little bit more about all the web language interactions going on behind the scenes.