IMMIGRANT TIKTOKERS DECOLONIZING ALGORITHMIC VISIBILITY

Authors

  • Daniela Jaramillo-Dent Erasmus University Rotterdam

DOI:

https://doi.org/10.5210/spir.v2022i0.13028

Keywords:

algorithm, immigrants, discourse analysis, moderation

Abstract

Immigration is deeply rooted in colonial structures that define who migrates and where, through a hierarchized perspective of the representations, knowledge, and ideas. It is possible to extrapolate these societal requirements to the digital space of social media platforms, where a combination of human and algorithmic moderation systems determine what is available, visible, and viral. Thus, colonial structures of dominance are perpetuated through coded biases and algorithmized oppression systems. The internal functioning of these moderation infrastructures is obscure, although we can glimpse at them through the contents and discourse of creators who describe their experiences with the platform, its algorithm, and the moderation policies that shape and affect their content creation practices. In this paper, we illustrate the different vernacular and platformed practices of immigrant content creators who portray the ways in which they negotiate their visibility with TikTok and its algorithmic system. The examples were extracted from a larger study that comprises 57 Latin American immigrant tiktokers who reside in the US and Spain. We use the concept of algorithmic (in)visibility as the basis for the study. The initial findings suggest that these creators deploy platformed practices such as the (re)use of audio tracks for visibility and protest; the use of TikTok vernaculars such as humor and sarcasm to convey controversial ideas; and partial deplatforming to protest the blockage of their profiles on TikTok. These practices provide insights about the decolonial negotiation of algorithmic (in)visibility taking place on social media platforms today.

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Published

2023-03-30

How to Cite

Jaramillo-Dent, D. (2023). IMMIGRANT TIKTOKERS DECOLONIZING ALGORITHMIC VISIBILITY. AoIR Selected Papers of Internet Research, 2022. https://doi.org/10.5210/spir.v2022i0.13028

Issue

Section

Papers J