User:Meikebrand/UTM
⌇⌇⌇⌇ UNRAVEL THE MEME ⌇⌇⌇⌇
Nora Mabrouki & Wille-Meike Brand, Nailed it
The meme ‘Nailed it’ was the starting point of the Unravel the Meme assignment. We started researching the history and analyzed it from different perspectives.
• Nailed It is a phrase used to express success after achieving something seemingly difficult with relative ease. It is often found as a caption on image macros or in sarcastic commentary criticizing the quality of success, especially in response to attempts at recreating recipes or craft projects. Mimicry involves the practice of “redoing” (the recreation of a specific text by other people and or by other means.)
Zina Burgers, Nora Mabrouki, Eunhyang clair Lee, Laura Lang, Lisa Vermeer, Laura Egger-Karlegger & Wille-Meike Brand
We grouped up with two other teams, we ended up with: 'Tatta's be like', 'Bad luck Brian' and 'Nailed it'. Based upon the three different meme's we came up with the theme 'stereotypes' (a stereotype is used to categorize a group of people. A set idea that people have about what someone or something is like.) From there we came up with the next three concepts/idea's: 1. Stereotype put in a box : Clair Lee and Laura Karl 2. Rotterdam-slang translater: Nora Mabrouki and Zina Burgers 3. Slang/stereotype chain of copy's: Räubomir Hotzenplotz and Meike Brand
While working on the projects we came to the conclusion that we had to re-formulate our theme. You need to know the context of a meme to fully understand it. For example, you need to know the dutch language and the dutch culture to understand 'Tatta’s be like'. So our new theme became Translate.
From there Laura Lang and I started working on our project, based on 'Tatta's be like'. We wanted to do something with copying/reproducing and how that changes the content. We started doing experiments with Google Translate, to see what the possibilities are in that format.
The first experiment was copying/reproducing with the use of Google Translate. The first step was reading one of the 'Tatta's be like' sentences out loud and let it be picket up by a voice dictation app, the app types the words you say in Notes. As you can see, the first step already causes a misunderstanding. After that we put the print screen in Google Image Translator and from there it translates the sentence to English. Then we let one laptop read it out loud to the other laptop, picking the sound up with the same program. With the sentence we searched for the first image in Google Images. A girl named Marijke Francis who was found dead after missing for years was the end result. As you can see, because of the steps we ended up with a totally different image than we started with. The repetition and misunderstanding caused this.
With this experiment in our minds we wanted to create a 'device' that would automate these steps, so people would be able to make the exact same steps in an easier way. We tried different auto mouse and keyboard softwares and created different versions. In the end we found a program called: Auto Mouse Click.
