Buckets of Rain
Back to job at hand...
It is never perfect
Once I hit the Processing land, I was daunted by task of collecting and displaying the movie posters. I was also having problems with the Netflix API. Since a Netflix users data is not public, apps have to authenticate (using oAuth mechanism) to retrieve user's data. I was making slow progress so I put shelved the idea to use movie posters and use just the Netflix dataset. So to refresh - the Netflix dataset has user ratings with the date of rating, rating given and movie name; no other data is available. But the sheer magnitude of the data makes it very interesting.
I overlooking was an salient variable in the Netflix dataset - how different is a user's rating from other users' ratings. Example, bob might rate Taxi Driver at 3. But the mean rating of all users might be 4.6. That is a signal of bob's uniqueness. (I don't know how someone can rate Taxi Driver less than 5).
So I went back to the drawing board and tried to come up with a more feasible visualization. I came up with the visualization below, where each movie is represented by a flower (sort of). The flower is ordered from left to right based on time of rating. I encoded the difference between the user's rating of a movie and the mean rating for the movie using a curve. The width of the curve indicates the difference in rating, the direction of the curve (left or right) indicates if the user rated higher or lower than the mean rating. So if all your flowers are leaning to the right then you rate higher than other users.
When the user hovers over a flower - I want to animate the flower to indicate the range of ratings. I haven't thought thru the math behind this, but I want the animation to indicate the range of ratings most commonly given to the movie by Netflix users. In other words the animation would indicate why the flower is leaning to the right or the left.- When the user hovers over a flower - the name of the movie, rating, etc will be shown in a popup dialog.
Now, if someone asks your movie taste, you can simply say "The answer my friend is blowing in the wind"
- In this visualization I'm not encoding many interesting variables like the time of rating by other users and number of ratings.
- Next - the x-axis is being used for indicating time of rating and agreement with other users. I don't this is a huge problem, but it might be confusing for some.
- Most importantly, there definitely is scope for more interaction.




