Untangling the Web of Deceit: Examining Shared User Susceptibility Across Five Types of Digital Deceptions

Objective To examine how domain-switching and user characteristics may predict broad susceptibility to digital deception. Background Despite successful automated filtering techniques, humans remain vulnerable to fraud, losing billions of dollars annually. Many scams are delivered by digitally mediated methods, such as phishing emails or fake social media accounts. However, research typically explores susceptibility to these deceptions independently, making it difficult to draw broad conclusions regarding susceptibility to digital deception. Method We recruited a representative sample to investigate how susceptibility to deception may vary across digital domains, particularly when switching between domains (i.e., domain-switching). Participants classified stimuli from five different digital domains (i.e., emails, text messages, news headlines, social media accounts, and voicemails), either randomly (i.e., domain-switching) or in separate blocks, and completed measures of cognitive reflection and digital literacy. Results The results suggest that when users struggle to discriminate between deceptive and legitimate stimuli in one digital deception domain, they are likely to struggle in others. Additionally, the results suggest that while cognitive reflection and digital literacy may help insulate users from deception, domain-switching may generally hinder user performance (i.e., slower responses). Conclusion Overall, individuals appear to be consistently vulnerable to deception across digital domains and this vulnerability can be exacerbated by certain task factors (e.g., domain-switching) and user characteristics (e.g., cognitive reflection and digital literacy). Application To develop more efficacious interventions that enhance user resiliency, research should consider broad training that incorporates correlates of susceptibility (e.g., cognitive reflection and digital literacy), and more realistic task settings (e.g., domain-switching).