Algorithms against corruption: A conjoint study on designing automated twitter 
posts to encourage collective action

Starke, Christopher; Kieslich, Kimon; Reichert, Max; Köbis, Nils

doi:10.31235/osf.io/wf45t

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Algorithms against corruption: A conjoint study on designing automated twitter posts to encourage collective action

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Köbis, Nils
Center for Humans and Machines, Max Planck Institute for Human Development, Max Planck Society;

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https://doi.org/10.31235/osf.io/wf45t
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https://osf.io/n65um/
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Citation

Starke, C., Kieslich, K., Reichert, M., & Köbis, N. (2023). Algorithms against corruption: A conjoint study on designing automated twitter posts to encourage collective action. SocArXiv, January 13, 2023.

Cite as: https://hdl.handle.net/21.11116/0000-000C-4489-D

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