Year: 2026
Type: article
Abstract: Digital platforms and social media shape social, economic, and political life, making participation almost unavoidable (Van Dijck, Poell, and De Waal 2018; Steinberg 2019). This platformization, driven by datafication, records and commodifies user activity for corporate profit (West 2019). While users perceive their engagement as private, they present a public persona that is subject to commercial and political surveillance (Baym and boyd 2012; Zuboff 2015). LGBTQ+ users face a paradox: social media is crucial for identity formation, community building, and self-expression (Robards et al. 2019), yet they encounter intensified algorithmic surveillance through content moderation tactics such as shadowbanning, demonetization, and account suspension (Are 2022; Bivens and Haimson 2016; Gillespie 2022). This study examines how LGBTQ+ users in Montréal and Berlin navigate platform regulations and resist algorithmic oppression via qualitative interviews with cultural producers, activists, and performers. Findings reveal two central themes: being seen and looking back. LGBTQ+ users are keenly aware of surveillance, exemplified by Astra, a Berlin-based activist, whose account was deleted after managing a queer collective’s social media. Confronted with inevitable monitoring, users adopt strategies like creating backup accounts, using alternative promotional methods, and deliberately defying censorship. This resistance is taxing; Sasha Kills, a Berlin-based drag artist, notes: “We don’t have a choice, and it is really unfair.” The research deepens data‑justice discussions by showing that resistance is not merely emergent but a mandatory practice for LGBTQ+ users in digital spaces. Ignoring surveillance jeopardizes their ability to benefit from platform affordances. In an era of platformization and the growing co‑optation of social structures, being excluded from platforms is a risk they cannot afford.
Source: Surveillance & Society
Author: Alex Chartrand
Institution: Concordia University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7165551249