Advertising-induced class cognition and social trust in platform societies: how algorithmic personalization reframes social comparison

Abstract

In contemporary platform environments, algorithmic advertising has become deeply embedded in everyday digital experience. For example, users browsing social media platforms such as Douyin, Instagram, or TikTok frequently encounter advertisements and influencer-driven branded content embedded within social feeds, such as luxury travel, high-end consumption, or entrepreneurial success. Because these advertisements are algorithmically personalized based on browsing behavior, interests, and social networks, they often present upward mobility narratives through socially proximate and relatable figures rather than distant elites. Over time, repeated exposure to such personalized aspirational imagery may subtly reshape how individuals interpret social hierarchy, mobility opportunities, and their own place within broader class structures. Despite this pervasive presence in everyday media environments, existing research has rarely examined how personalized advertising environments influence individuals’ cognitive perceptions of social stratification. Yet existing research primarily conceptualizes advertising as a commercial persuasion tool, overlooking its broader social-cognitive consequences. This study advances an algorithmic cognitive mediation framework to explain how personalized advertising reconstructs class imagination and contributes to generalized social trust in platform societies. A key methodological contribution of this study is the development and validation of the Advertising-Induced Class Cognition (AICC) scale, a newly constructed 12-item measure capturing three dimensions of platform-mediated class perception. We introduce AICC as a core cognitive mechanism capturing individuals’ algorithmically mediated perceptions of mobility opportunities, symbolic class proximity, and aspirational alignment. Using a large-scale national survey of 5, 487 Chinese internet users and structural equation modeling with instrumental variable robustness checks, we find that personalized advertising exposure is positively associated with social trust through AICC. Moreover, this mediated relationship is conditionally shaped by digital socialization, exhibiting an inverted U-shaped pattern in which individuals with moderate platform integration experience the strongest cognitive influence. The findings extend social comparison and trust formation theories by revealing how algorithmic personalization may reshape upward comparison processes and embeds commercial content within the cognitive infrastructure of social trust. This study contributes to platform society research by repositioning advertising not merely as market communication, but as a formative social force shaping class imagination and social cohesion in digitally mediated environments.