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Emma

Emma | Stomp Out Bullying | Grey
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basics
Industry: Beauty & Health
Media:Cyber
Style: Minimalism
descriptioncnen
Why is this work relevant for Creative Data?

There have been studies done on the impact of cyberbullying on the brain and how it correlates to risks of suicide and self-harm, but only after the fact. But never have people been able to see the impact of cyberbullying in real-time. By translating complicated data, scales, and various levels of toxicity into a simple and creative visual device, it allowed the average teen, educator and parent to visualize the impact cyberbullying has on a teenager’s brain.

Describe any restrictions or regulations regarding Health & Wellness communications in your country/region including:

N/A

Health & Wellness work must demonstrate how it meets the criteria 'life-changing creativity'. Why is your work relevant for Health & Wellness?

Teens don’t know the impact cyberbullying has on their brains and their parents don’t know about the progressive impact it can have, until it’s too late. To educate teens, educators and parents about the impact cyberbullying can have, we needed to find a way to translate complicated and dense data in a way that wouldn’t just tell our target about it but show our target what that impact really looked like.


Background

According to the National Society for the Prevention of Cruelty to Children, in just a five-year period, there has been an 88% increase in cyberbullying. And the likelihood of self-harm and suicide increases more than 2x because of cyberbullying, but people don’t recognize are the devastating consequences cyberbullying has. Until it’s too late. We needed to help people see the impact cyberbullying has on our youth.

Describe the idea/data solution (20% of vote)

To bring Emma to life, we needed hundreds of thousands of data inputs that would mirror what the average teen is exposed to online on an everyday basis. To get this, we interviewed teens about their online behaviors and created a series of ethnographies based on their data consumption. We mined the websites, apps, and hashtags they were exposed to and created a digital shadow of their daily online lives.

From there, based on the data we gathered and a recent clinical study, we created a machine learning based sentiment analysis tool. It allowed us to categorize toxicity levels in each individual comment. High levels of toxicity were then translated to palpable information in Emma’s vitals.

Data was the source of the insight as well as the medium that expressed the idea. By correlating Emma’s vitals with actual biological markers from the study, the project allowed us to not only raise awareness, but develop an education tool that can help teach teens, educators and parents about the real-time impact of cyberbullying.



Describe the data driven strategy (30% of vote)

Based on interviews with teens, we used a wide range of data scrapping tools that gave us access to the hundreds of thousands of comments our teens are exposed to online. We searched multiple platforms including, but not limited to, Facebook, Twitter, Instagram, Reddit, Twitch, and various blogs, and then collected a dataset comparable to the average monthly exposure of a teenager.

Then using a recent clinical study by Erin Burke et al. Peer Victimization and its impact on adolescent brain development and psychopathology, we created a direct correlation between highly toxic comments and the decrease in Emma’s ability to process negative comments.

After running Emma’s simulation based on the clinical study findings, Dr. Jeff Gardere, a clinical psychologist, helped us create a narrative using the data points to correlate them with Emma’s event horizon.


Describe the creative use of data, or how the data enhanced the creative output (30% of vote)

The key component in building Emma was the machine learning sentiment analysis model that we used to identify toxic comments. The model was based on the dataset provided by the Conversation AI team from Google and used six different labels to classify the comments: Toxic, Severely Toxic, Obscene, Threat, Insult, Identity/Hate.



List the data driven results (20% of vote)

After 52 hours of processing more than 150,000 comments, the memory allocated for emotional analysis in Emma’s brain ran out. By eroding Emma’s ability with every toxic comment, a vicious cycle was created, much like a teenager’s brain, where we learned that escaping the echo chamber of bullying is impossible, if persistent. Parts of the human brain are hindered by a loop of negativity with measurable physical results. We recreated this loop by removing vital memory allocation in Emma’s processing power, eventually resulting in a shutdown.
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