IN THE ERA OF SELF-EXPRESION, OVERSHARING, OVER-EXPOSURE,

AND OVERFLOW OF OPINIONS, HATERS COMMENT. HATERS HATE.

HATERS HURT.

And teenagers are the most affected group, sometimes suffering from depression or even tragic endings.

BRIEF: To become a badge brand for GEN Z by BEING CULTURALLY RELEVANT.

OBJECTIVE: Increase brand awareness and boost transactions.

The teenage years are a transitional period characterized as being volatile both emotionally and physically. Core personality traits such as thoughts, feelings and behaviors are defined by our experiences. By who we talk to, what we read, and how we´re treated. Spending up to nine hours a day on social media, teenagers are exposed to an occasionally hostile environment and susceptible to adopting bullying behaviors or becoming the victim of a bully.

As part of Sprite’s #ILOVEYOUHATER campaign, we wanted to engage with Sprite´s teenage target audience by being relevant and creating a one-of-a-kind experience. We decided to conduct a social experiment by bringing a real hater face to face with his victims.

Via the Twitter API, we downloaded 15,000 tweets from Argentines notorious for being bullies or being bullied. Their conversations, along with a proprietary dictionary of Argentine Spanish words and phrases that helped us navigate a complex jargon and decipher the connotation of each tweet, trained our machine-learning model.

Once the training was completed, we had it process more than five million tweets from over 100,000 unique users from Sprite´s Twitter community and other brand accounts with a high affinity with Sprite´s teen target. Classifying each tweet as offensive or non-offensive and differentiating the haters from the non-haters.

To better understand our audience and the current context of bullying in Argentina, we used natural language-processing techniques to determine the over-arching themes used by haters to assault their victims. We identified five topics:

1. Ideology (Personal opinions regarding hot-button social and political issues)

2. Body Shaming (Physical attributes)

3. Trolling (Generic insults used just to insult)

4. Gender Warring (Machismo, feminism, gender violence)

5. Identity (Nationality, race, economic situation, education)

Finally, we generated a scoring based on the frequency of each type of insult, and the topic they pertained to, achieving a final ranking of all the identified haters.

During the course of two-months, we developed and trained a custom machine-learning algorithm using 15,000 tweets from key seed users (Argentines notorious for being bullies or being bullied) and a proprietary dictionary of Argentine Spanish words and phrases.

Once the training of the model was completed, we had it process more than five million tweets from over 100,000 unique users from Sprite´s Twitter community. Classifying each tweet as offensive or non-offensive and differentiating the haters from the non-haters.

To better understand our audience and the current context of bullying in Argentina, we used natural language-processing techniques to determine over-arching themes used by haters to assault their victims. We identified five topics: ideology, body shaming, trolling, gender warring, and identity. Finally, we generated a score based on the frequency of each type of insult, and the topic they pertained to, achieving a final ranking of all the identified haters.

While online bullying is a global issue and already extremely relevant for our target, we wanted to take it a step further by using real people.

@AguanteElCofler ranked highest among our list of haters so we contacted him invited him to participate in a once in a lifetime experience brought about by Sprite. Once our hater was onboard, we reached out to everyone he had criticized during the previous six months.

For the day of the encounter we had personalized t-shirts made for each victim to wear – displaying the insults they received on Twitter from @AguanteElCofler.

We filmed the encounter and distributed the three-minute video across the most relevant digital media channels for our target: YouTube and social media platforms.

With no media budget, we relied solely on word of mouth and organic shares to create scalability of our message.

+30MM TWITTER ORGANIC REACH

+20MM EARNED MEDIA

#1 TRENDING TOPIC

0 MEDIA INVESTMENT

“Watch this for heart refill”, Sarah Silverman.

“Sprite puts a hater in front of their victims”, Rachel Sheherazade.

“Sprite’s terrific campaign”, B.L. Ochman.

“Incredible campaign”, Raissa Chaddad.

“Hatred can be avoided ”, Manuela Dalvia

“Sprite attack haters with love”, Edith Brou.