Abstract
Implications of algorithmic mediation can be studied through the artefact itself, peoples’ practices, and the social/political/economical arrangements that affect and are affected by such interactions. Most studies in Academic social media (ASM) focus on one of these elements at a time, either examining design elements or the users’ behaviour on and perceptions of such platforms. We take a multi-faceted approach using affordances as a lens to analyze practices and arrangements traversed by algorithmic mediation. Following our earlier studies that examined the artefact, this study’s aim is to understand how algorithmic mediation in ASM may shape researchers’ perceptions. We conducted online in-depth interviews with show and tell (n = 11) with ASM users from four countries, about their use of ASM. Data were analyzed using thematic analysis, and the codes were clustered in themes and validated via peer debriefing process. Four themes—related to exposure to content, visibility, ethical or legal infringements, and engagement—are discussed considering implications of datafication and findability. We conclude that algorithmic mediation constructs a narration of the relevant other in ASM, configuring the other as participatory and productive.
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Notes
Dossier number G-2019 09 1745 (Belgium); CAAE number 38406720.2.0000.5347 (Brazil).
The interview script can be found in Monteiro-Krebs et al. (2022, p. 253).
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Monteiro-Krebs, L., Zaman, B., Geerts, D. et al. Every word you say: algorithmic mediation and implications of data-driven scholarly communication. AI & Soc 38, 1003–1012 (2023). https://doi.org/10.1007/s00146-022-01468-1
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DOI: https://doi.org/10.1007/s00146-022-01468-1