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Breaking the Tinder Code: a personal experience Sampling method of the Dynamics and influence of system Governing Algorithms

Breaking the Tinder Code: a personal experience Sampling method of the Dynamics and influence of system Governing Algorithms

Abstract

This short article conceptualizes algorithmically-governed platforms as positive results of a structuration procedure involving three kinds of actors: platform owners/developers, platform users, and device learning algorithms. This threefold conceptualization notifies news results research, which nevertheless struggles to add algorithmic impact. It invokes insights into algorithmic governance from platform studies and (critical) studies in the economy that is political of platforms. This process illuminates platforms’ underlying technical and logics that are economic makes it possible for to make hypotheses as to how they appropriate algorithmic mechanisms, and exactly how these mechanisms work. The current research tests the feasibility of experience sampling to test such hypotheses. The proposed methodology is put on the scenario of mobile dating application Tinder. Continue reading