#metoo voices

code literacy & physical computing

#metoo voices is an interactive sound installation representing the Twitter #metoo movement.

my role

Interaction Designer & Developer
Concept, physical computing, coding on Arduino, JavaScript and Meteor App, and video shooting and editing.

TEAM

Glenda Capdeville & Kate Styer

ADVISORS

Bruno Kruse, Carrie Kengle, and Eric Forman

date

October–December 2017

Concept

In 2006, activist Tarana Burke began the “Me Too” campaign to encourage “empowerment through empathy” in support of women of color, especially in underprivileged communities, who had experienced sexual harassment or assault. Burke believed that survivors could help each other heal by showing each other that they were not alone, that there were other people who had gone through it, too.

In October 2017, on the social media platform Twitter, actress Alyssa Milano used the words “me too” as a hashtag in a tweet in a response to multiple women coming forward to share their experiences of sexual assault committed by Hollywood producer Harvey Weinstein, and encouraged others to use the hashtag too. The hashtag exploded–it was used more than 1.7 million times within just a few days by users sharing their personal experiences with sexual assault.

Using Twitter’s API, the installation counts how many times the hashtag #metoo has been tweeted or retweeted. When a participant says “Me too!” into the megaphone, the installation counts the number of instances of the hashtag has been used in the last minute and plays recordings of people saying “Me too!” in that number.

#metoo voices creates a physical representation of the #metoo movement by transforming words on a screen into human voices. It also emulates the experience of sharing a painful story and knowing immediately that you are not alone.

How it works

#metoo voices is built with the following components:

Sound detection sensor module
Arduino
Music Maker MP3 shield for Arduino
8 ohm speakers
Amplifier module
Meteor JavaScript web framework written using Node.js
Twitter API

Check out our code here.

The sound detection sensor module reads the volume of sound from the megaphone when a user says “me too”, per a threshold set in our Arduino code. When that threshold is met, the value is sent to our Meteor app, which is connected to Twitter’s API and tracking instances of the #metoo hashtag. When the value is received, the app counts how many times it has been used in the last minute, then sends that value back to Arduino. Arduino then plays pre-recorded files of anonymous voices saying “me too” in that value.