Abstract
The proliferation of artificially generated images has introduced a new class of visual propaganda referred to as deepfakes, which can deceptively mimic reality and manipulate perception on a massive scale. Although propaganda is hardly a new social problem, the emergence of deepfakes necessitates an interdisciplinary response from the social sciences as well as cyber/computer sciences. In this study, the research team revisited long recognized propaganda categories to determine which types were most impactful across X.com with a focus on the 2024 U.S. Presidential Election. Working from a data set of 202 politically charged deepfakes, images were classified across 17 classic propaganda techniques (e.g., bandwagon, fear, transfer) and a propaganda impact score was introduced to quantify impact, which was a composite metric integrating reach, sentiment, and toxicity. The results of this study show that the propaganda categories of preemptive framing, deification, and bandwagon disproportionately shaped engagement and emotional response. Put differently, the results of this study showed that the most virally effective images are not necessarily the most toxic, but rather those that strategically pair emotional resonance with algorithmically optimized reach. Thus, a key takeaway from this study for cybersecurity and security professionals who are charged with combating disinformation in various spaces is that particular types of propaganda are more effective and dangerous to eliciting emotional responses relative to others.
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