Reconstructing Authenticity in Synthetic Media: Conceptualising the Impact of Deepfake Realism and Novelty on Advertising Value, Trust, and Engagement
(A2026-134297)

AUTHORS

AHMED GEEBREN, Northumbria University; Shenaz Rangwala, Northumbria University

ABSTRACT

Deepfake technologies are reshaping social media advertising, yet little is known about how consumers interpret synthetic brand content, or which perceptual cues drive their responses. This research conducts with an exploratory qualitative study to identify the attributes consumers attend to when evaluating deepfake advertising. Findings reveal three key factors, realism, novelty, and perceived disclosure, that strongly influence perceptions of advertising value, which subsequently shape trust and engagement. Building on these insights, the paper proposes a conceptual framework explaining how deepfake attributes affect consumer evaluations and how disclosure moderates these effects. The study contributes to advertising and digital persuasion theory by clarifying the mechanisms underlying consumer responses to synthetic media and highlighting the fragile role of trust in deepfake contexts. A follow-up quantitative study will empirically test the proposed model.