The algorithmic persuasion framework in online communication: conceptualization and a future research agenda

Purpose: 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). Design/methodology/approach: 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. Findings: 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. Originality/value: 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.