Data visualization can be for the better or the worst. Therefore, understanding its pillars is at the nub of the translation of text into visual language. At the crossroads of design and a more literary approach, these data visualization are the result of an always different understanding process, depending on the text itself, and the chosen form.
A research process based on data.
As a group, we explored a wide database gathering metrics about around 4 000 films. From numbers and text to data visualization we used tools such as RawGraph and OpenRefine to answer questions such as: What is a popular film? What characteristics do popular films have? How does the popularity evolves depending on the geographical zones? How does the popularity evolve through time?
