This is a Very Hard Video for Me to Make /
Queer Identities Through Algorithmic Taxonomy video essay

(2022)
Facebook offers 58 options to describe one's gender. These labels can be seen as progress in the emancipation of queer gender and sexual identities - while at the same time they can serve to disguise the commodification of the user.

Our subjectivities live in the context of surveillance capitalism, an economic system centered around the harvesting of personal data for the core purpose of profit-making. The myth of a universal man as the consumer prototype has been overcome by the online profile processes which are concerned with our psychological attributes, personality traits and lifestyle. These mechanisms translate into meticulous tailoring of ads and content - the hyper-customisation of our digital experience. We find ourselves in a coercive loop of self-creation which demands us to categorise or be categorised into specific identity boxes.

Our case study is a deconstruction of coming out videos on YouTube. Starting to emerge in 2014, they acted as an important form of representation and a means to form a community for the LGBTQI+ youth. The vast majority of the videos, however, seem to follow a rigid template, creating a distinct genre/typology. Despite the formulaicness of the format and the apparent performativity displayed on camera, the described experiences can be radically different as they are inextricably linked to the socio-economic background of their authors.
The templatization of individual experiences on YouTube is, in a way, a logical continuation of a process that started in the 19th century: the transformation of gender and sexuality from a set of behaviors into an all-encompassing social identity.

As Foucault stated, “[...]the homosexual was now a species.” But how is this species - a queer social identity - shaped in the 21st century, caught in the #label-induced echo-chambers of algorithmic platforms, where the subjects are profiled and thus produced through the commodification of their data?

made in collaboration with Berta Grau and Sara Levarato