CINEMATIC CURSING DATA VISUALIZATION
I want to start off by saying that I don't think cursing makes a good film a great film, but I do think that cursing in movies does help us connect (not that I can relate to a hit man in a Tarantino film). Cursing helps lower stress and you feel a certain level of catharsis when you release a "fuck" under your breath after a long day, hour, or even few minutes.
INSPIRATION
I'm not 100% sure how this idea started in my head during Journey Week, even after looking at my early notes on the idea. I remember exploring how I could use data to represent something involving movies. I believe the next part was a separate thought... how could I use data with CMYK? The numbers could translate into colors. What numbers can I get from movies? What is something unusual that would get someone's attention and interested in this data? Cursing?
Aren't you curious to know what films have the most shits uttered? Or how the cursing in the first film varied in the sequel? Or if two similar movies of the same genre from the same time had similar cursing? If the cursing is translated into values of CMYK, then you would be able to see how curse-filled each film was and easily compare any film visually. I had a solid idea. Then it was deciding what words to use. I figured 4-letter words would be the most prominent and therefore create the boldest colors. I went with shit, damn, hell, and fuck. And I assigned each, in order, their color: cyan, magenta, yellow, and black.
COLLECTING THE DATA
I knew collecting the data could be tedious. I searched the web, thinking that someone out there had to have collected this at some point. I found many contradicting counts for the films with the highest curse count (Pulp Fiction, Wolf of Wall Street, etc.). I thought the companies that did subtitles would have some data open for me to explore. Not for free. So I decided to do it on my own. I made a giant list of movies and began searching for scripts. As I found the scripts, I clicked ctrl+f and started searching for some words and handwriting a list. I added other movies as I thought of them or found scripts.
THE SNAGS
It may not come as a surprise, but a lot of movies use certain words more than once, especially the F-bomb. I think once there's the freedom to use it in an R-rated film, they just roll with it. The issue with this is that any film with 100+ f-words would have a K value of 100 and be black. And that wouldn't be very exciting or colorful. I had an idea using multiple layers in Photoshop and setting them to "multiply", but that got confusing and just felt like I was making up rules to make it look nicer. There was also issues that some words tended to only be uttered handful of times in most films. The solution to fix both of these issues was to create base multipliers for each word/value. This would allow the films to be still be compared by color and keep me from losing quite a few films that would have turned completely black. It would also allow for a wider range of colors.
THE MULTIPLIERS
Using my basic Excel skills allowed me to take the data I already had entered and multiply each color by its new multiplier. Each multiplier was based on the film I had chosen to be the 100 for each color. This tended to be the one with the most uses of the word, except for FUCK. For example Fear and Loathing in Las Vegas had the highest value for DAMN with 50 uses in the film, so the multiplier for that word was x2. If a film used the word 25 times, its cyan value would be 50. South Park uses HELL 56 times, so it's multiplier is x1.7857. Superbad uses SHIT 76 times, so it's multiplier is x1.3157. And Straight Outta Compton uses FUCK 184 times, so to normalize this word the multiplier is x.54347. Excel did all the math for me and gave me the value for each of the four colors for all 100 or so of my films. For example, Bad Santa's word count of 3, 50, 2, 154 (DAMN, SHIT, HELL, FUCK) would have a CMYK value of 6, 66, 4, 84. A beautiful deep dark sugar plum.
I also decided at this point that the saturation of each film's color would represent the rate of curing in the film. More cursing should be more colorful, right? The percentage on the AR layer is the level of saturation. South Park had the highest rate of 2.825 curse words per minute (of the four used in this project). That was the baseline for 1 or 100% since you can't saturate more than 100%. All other rates were divided by 2.825 and multiplied by 100 to get their saturation percentage.
THE PRESENTATION
While collecting the data I was brainstorming the best way to present it so that it was fun, cinema-related, and visually appealing. Multiple movie posters. I would group the films into genres: action, comedy, award winners, and horror. This would also help me see how many films I could fit based on length of title and size of the text. I was able to eliminate some of the longer titles and lay out how many would fit on a page at a legible font size.
I also felt that by being on movie posters, it would feel like you were walking through a theater and looking at the coming attractions hanging on the wall. This is also when I started to consider another layer to this project. AR would allow you to see the stats under the titles and calculate that film's CMYK values to recreate them. I also felt that there was space on the posters that could be filled in with some fun, basic illustrations from some of the films.
THE ILLUSTRATIONS
I made 42 illustrations so I had wiggle room if I had to adjust what films worked on the posters. I wanted enough variety, but also wanted some films that were similar in color. I used a decent amount of the illustrations. Not every film on each poster had their illustration added. And there was no exact number I wanted on the posters. It was all based on what fit and looked right.
THE POSTERS
At this point, I had all of my illustrations done and the titles colored, ready to drop in. I had created the header and footer for the posters. I used the bottom section where the credits usually are as a place to explain how the data works when you use the AR. Each genre covered a curse words. This also meant you had to interact with at least 4 posters to learn every multiplier and solve for each part of CMYK to learn the films' color formulas. Based on the number of films and how they all fit onto the posters, I determined there would be 7. Award winners, comedy, and action would each get 2. Horror would have a single poster. Some of the placement isn't the most satisfying thing to look at, but it was the text and data I had to work with in the space.
I encountered some problems using Adobe Aero. Even with a new computer, the graphics card had to be shut off for the program to function. And even when I did this and got it working, it failed to export functioning QR codes to put on the posters that would activate the AR. This is a video demonstrating how the AR would look on the posters.
I enjoyed working on this project, especially doing the calculating and illustrations. I do not see myself using Aero again any time soon. As far as the posters go, I think they convey what they are supposed to and allow viewers to compare something they never thought they could compare with colors. I'm not 100% loving their look, but as I said before some titles did not lend themselves well for the layout and placement. But overall, I think this came out pretty well.
fin.
KYLE LUTZ - EMERGING MEDIA - PROF. MILLER - SPRING 2021
Credits:
Created with images by onkelglocke - "cinema curtain theater" • Efraimstochter - "film reel 16mm film"