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This chapter provides an overview of what is currently known in the scientific literature about the effects of disclosures of sponsored content on consumers’ responses.

We provide a qualitative literature review of 21 empirical studies.

Awareness of disclosures is rather low, but when consumers are aware of a disclosure, it successfully activates persuasion knowledge and can increase brand memory. The literature shows inconclusive findings with respect to the effects of disclosures on attention paid to sponsored content, critical processing, brand attitudes, and purchase intentions. In addition, the literature shows that modality of the disclosure has no significant effects, but the content of the disclosure, its timing, its duration, receivers’ moods, and their perceptions of the sponsored content or the endorser are important moderators.

More research is needed on differences in effects of disclosures in different media and on disclosures of online sponsored content online (e.g., sponsored tweets and vlogs).

This chapter provides advertisers with insights on how disclosures affect the persuasiveness of sponsored content in several media.

For legislators, explicit guidelines on how to create effective disclosures of sponsored content are provided. For example, to increase persuasion knowledge, disclosures should be portrayed for at least 3 seconds and if logos are used, they should be accompanied by texts explaining the logo.

This overview is a valuable starting point for future academic research in the domain of disclosure effects and provides insights for advertisers and legislators.

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.