Algorithmic Ghettoisation: Social Media Algorithms and the Crystallisation of Collective Identities in Fragile Societies

This article examines how social media platforms, through their algorithms, shape collective identities in fragile societies through the concept of “Algorithmic Ghettoization.” It argues that, contrary to platforms’ emancipatory promise, algorithmic infrastructures can deepen pre-existing societal fault lines and harden them into relatively closed blocs, particularly under conditions of uncertainty and crisis. Departing from standard “echo chamber” and “filter bubble” accounts, it offers a mechanism-level explanation that jointly considers regimes of visibility, engagement incentives, and platform governance. The mechanism’s initial threshold is the technical narrowing of encounters with opposing views, which displaces the “other” from being a recognized interlocutor within relations and recasts them as a figure made legible through labels and representational templates. Drawing on and synthesizing insights from Simmel, Bauman, and Lamont, the article conceptualizes ghettoization as the contraction of arenas of encounter and the “crystallization” of identity performances. In crisis moments, identity performances rewarded by circulation are compressed into shorter, sharper, and more reproducible forms, reinforcing the “us–them” divide. Finally, it underscores how governance design and moderation capacity condition the speed and durability of these dynamics.