The project I’m working on is an exercise in self-expression and an investigation into the intersection of online identity, algorithms, digital footprints, and screens using Spotify as the place of exploration.
For my project I started off wanting to continue to explore ideas around identity, the internet, and the digital. This led me to consider the way streaming sites like Spotify contribute to the way people enact their identities through the consumption of music.
An article I read as part of my research entitled Crafting online identities: Active and reflexive identity work on Spotify states that “the development of on-demand music streaming platforms, such as Spotify, Apple Music and Pandora, have transformed the dissemination and consumption of music. These networks provide open forums for listening, sharing, rating and recommending music. They have the ability to shape music consumption in ways not previously encountered. These online music streaming services not only offer instant, ubiquitous access to vast catalogues of music, but they also have the potential to influence what music users listen to and the ways they consume it. By collecting a vast amount of user data on music choices, listening habits and interactions, computational techniques, in the form of recommendation algorithms, can recognise and predict the similarities and differences in musical preferences of an entire user database. These recommender algorithms help structure the large and diverse array of possible song choices, but they also have the ability to influence the music that individuals are and are not presented with on an increasingly personalised basis.”
This got me thinking about Spotify wrapped which is an annual feature offered by Spotify. It typically becomes available towards the end of each year, summarizing users' listening habits over the past twelve months. It provides users with personalized statistics such as their most-streamed songs, artists, genres, and total listening time. Additionally, Spotify Wrapped often includes a curated playlist based on users' listening history. Users can share their Wrapped summaries on social media platforms to showcase their music preferences. I feel like a lot of people anticipate sharing their Spotify wrapped summaries at the end of the year and that it feels like a way of showcasing an important part of themselves to their followers and friends on social media.
With this project I wanted to examine how users curate their online identities through their music choices, which taps into broader questions about the construction and performance of identity in the digital age, and I wanted to approach this from a personal place by creating a sort of self portrait of myself as a pixel.
By providing personalized recommendations and curated playlists, Spotify not only shapes users' musical preferences but also influences how they present themselves to others online. This got me thinking about how much of what I listen to, and have listened to throughout the years, was based on my actual preferences and how much of it was based on algorithmic recommendations. From here, I decided to compile all the number one most listened to songs of mine from my Spotify wrapped between 2018 and 2023. I listened to these songs and noticed their similarities and differences. I decided I wanted to express myself through these songs by the vocals from each of the songs accompanying them with music I have created.
I also decided to make my own music for this project using samples that I purchased from other artists. I did this as a way of communicating parts of myself and the way sharing happens on the internet.
Lastly, as I mentioned, I wanted to create a self-portrait of myself as a pixel. I wanted to do this as a way of representing the way in which I am only a small part of a larger community of people who use these streaming sites and informing these recommendation algorithms. The pixel is represented as a 5x5 foot cube. The cube will have screens on each side of it that will display synced video of glitched images while glitchy music that I have created plays.