Twitter Town examines how fake news has become so prevalent that distinguishing between what is real and fake is becoming increasingly difficult. Recently, “reputable” news sources have reported fake news as real, which then was further distributed by social media users, and even other news sources. On December 5, 2016 a man with an assault rifle entered the Washington D.C. restaurant Comet Ping Pong to “self-investigate” Pizzagate, a fake news story that was perpetuated by social media, and was even tweeted about by General Mike Flynn (Donald Trump’s pick for national security adviser). This virality has been incorrectly attributed by large amounts of the public as an indicator for accuracy.



Four week graduate school project.

Specification: Simulation, game app, speculative design


Execution: Unity, C#, Javascript, Json, Illustrator, After Effects, Photoshop, Android, Twitter Api

Piece: Twitter Town is a game app where users can try to battle the virality of fake news by adding/ sharing real news to eliminate it.


Things in bold are key points




_Process

Twitter Town was started with a trip to the Salton Sea. On the way there my car got a pretty severe flat tire and left me (and four other classmates) stranded in the Inland Empire, CA. But while waiting for the repairs, I was killing time looking at facebook and twitter. During this time I came across a few articles relating to fake news. The first was discussing how students could not differentiate between real and fake news. The second was an article about how CNN aired 30 minutes of pornography, and that FOX news actually reported that it was true. (it was not true, and they changed the article) The third article, mentioned above, was about what is now called Pizzagate, where a man with an assault rifle entered a restaurant to “self-investigate” a child sex ring based on false information.

1_ https://www.npr.org/sections/thetwo-way/2016/11/23/503129818/study-finds-students-have-dismaying-inability-to-tell-fake-news-from-real

2_ https://www.foxnews.com/entertainment/2016/11/25/porn-accidentally-airs-istead-cnn-in-boston-for-30-minutes.html

3_ https://dcpizzagate.wordpress.com/3b//

https://www.nytimes.com/interactive/2016/12/10/business/media/pizzagate.html?_r=0

These three articles really pointed out a near future tipping point, that in many ways is already starting to unravel, where the distinction between real news and fake news will be completely impossible to make. It would become complete chaos, and no one would be able to tell what is true.

I wanted to explore this concept through a simulation where I would be able to populate the simulation with actual live tweets. Twitter is a big factor in the virality of fake news, and the idea that a single tweet can spread so much false information made it seem like the perfect foundation for my simulation.

I quickly realized that the twitter API is extremely difficult to work with, and that many have tried and failed. However after several days of searching and altering code, I found a Unity project that accessed Twitter's API. After a little more work (another day or so) I got the Unity project to pull tweets, from a location specified by the user, and to display them on screen.

        Initial simulation with place holder tweets.


        Live Tweets being displayed in Unity.


      Further exploration of the initial simulation.

But by this time in the project I realized that my simulation wasn’t so much a simulation as a infographic, and more importantly it wasn’t exploring the virality of fake news and its consequences/outcomes. I started to research virus simulations and found one that explored similar behaviors that I felt fake news portrayed, and began working on redesigning and altering the behaviors to further explore my concept. I explored a few different behavior through this simulation beyond. There was the obvious, where fake news and real news exists, and that in some cases one becomes superior to the other. But more interestingly the simulation revealed how fake news could become real news and that not every time does fake news defeat real news (and sadly vice versa).

      Initial game. Me exploring how it was built.


    Initial game. Me exploring how it was built.

    Encountering bugs and bad code.

_Critical Reflection

In future iterations I would like to get the Twitter API aspect of the project working. Specifically, I want to get the search parameters to allow the user to input a hashtag, and populate the simulation with tweets related to that hashtag. Once the tweets are pulled from the API the script will then sort the tweets into real or fake news, allowing the user to play the game with actual real or fake news. Then finally the script would take screen captures of the game and post that generated “news” back onto Twitter.

However the game as a sketch that explores the concept of fake news as a future tipping point is pushed as far as I think I can take it. Adding levels, with new barriers, might help further explore the different factors that contribute to the virality of fake news, and maybe even shine light on how we, as contributors, could eliminate this issue. I think further iteration of Twitter Town would be an interesting exploration. After learning more C# and Javascript it might be interesting to revisit Unity and further create Twitter Town as a bigger more complicated game or simulation.


Key Points:


Students could not differentiate between real and fake news

CNN aired 30 minutes of pornography (fake), and that FOX news actually reported that it was true.

Pizzagate, where a man with an assault rifle entered a restaurant to “self-investigate” a child sex ring based on false information.


These examples define a near future tipping point where the distinction between real news and fake news will be completely impossible to make.


Wanted to explore this concept through a simulation populated by live tweets.










































































































I realized that my simulation wasn’t so much a simulation as a infographic, and more importantly it wasn’t exploring the virality of fake news and its consequences/outcomes.


But more interestingly the simulation revealed how fake news could become real news and that not every time does fake news defeat real news (and sadly vice versa).


















Redesigning the game.


Perfecting the behaviors.


Perfecting the behaviors.




At this point the game had in many ways reached the limit that it could explore the concept, So I decided to start exploring what Twitter Town would look like. I started explore this by envisioning landmarks in Twitter Town as hashtags and sketching out how they would look within the restraints of an artboard that was the size of a iPhone. Below is what I came up with.

_Brief
The "tipping point" is a common term to signify "the moment of critical mass, the threshold, the boiling point" (Malcolm Gladwell). In this studio we are using this term to represent moments when a force (natural, technological, social) reveals its present and future impact through a collapse or break of some sort.

Consider the ways in which the project is a form of "world-building": every single decision of what to include and its appearance should be determined based upon the specific logic of the scenario and ultimately support the central idea of the project.

We are interested in examining the potentials of simulation in a design (rather than engineering or entertainment) context, so part of the project is to develop an argument about how this is different/useful/generative.

The simulation and the world it exists within can be 3D or 2D, but it must be visual. Please keep in mind that by the word “simulation” we are not intending for you to merely produce animations: elements should inter according to the rules you assign to them. Be sure to allow a period of discovery where the emergent effects can be observed and manipulated.




   

_Tools
Unity, C#, JavaScript, Json, Illustrator, After Effects, Photoshop, Android, Twitter

All works © Michael Milano 2010-2019. Please do not reproduce without the expressed written consent of Michael Milano.



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