The purpose of this study is to introduce a comprehensive and dynamic framework that focuses on the role of algorithms in persuasive communication: the algorithmic persuasion framework (APF).
In this increasingly data-driven media landscape, algorithms play an important role in the consumption of online content. This paper presents a novel conceptual framework to investigate algorithm-mediated persuasion processes and their effects on online communication.
The APF consists of five conceptual components: input, algorithm, persuasion attempt, persuasion process and persuasion effects. In short, it addresses how data variables are inputs for different algorithmic techniques and algorithmic objectives, which influence the manifestations of algorithm-mediated persuasion attempts, informing how such attempts are processed and their intended and unintended persuasive effects.
The paper guides future research by addressing key elements in the framework and the relationship between them, proposing a research agenda (with specific research questions and hypotheses) and discussing methodological challenges and opportunities for the future investigation of the framework.
