Engaging tourists from city aesthetics: evidence from multi-modal analysis of computer vision and text mining

Purpose This study investigates the evolution of city branding strategies in the digital era, focusing on how aesthetic design elements in city marketing content shape user interactions on social media. It examines how visual design attributes in city imagery drive engagement and uncovers the psychological processes underlying these effects. Design/methodology/approach Drawing on cue utilization theory and emotion as social information (EASI) theory, the research employs multimodal machine learning to analyze a comprehensive dataset from city marketing organizations. The study utilizes computer vision algorithms and natural language processing to deconstruct visual complexity into three dimensions: feature complexity, compositional complexity and color variety. A negative-binomial regression model is applied to examine the relationships between visual complexity, emotional responses and user engagement. Findings The findings reveal that feature complexity and color variety exhibit an inverted U-shaped relationship with user engagement, while compositional complexity demonstrates a U-shaped relationship. Additionally, user emotional responses significantly mediate the impact of feature complexity, compositional complexity and color variety on user engagement. These results highlight the nuanced effects of visual complexity on user behavior and the critical role of emotional responses in this process. Originality/value This study expands the knowledge boundaries of visual marketing through three layers of innovation. First, it overcomes the traditional limitation of treating visual complexity as a unidimensional construct by proposing a triadic analytical framework of “Feature-Composition-Color” tailored to the characteristics of city marketing. This framework uncovers the asymmetric impact mechanisms of different dimensions on user engagement, offering new insights into the long-standing “complexity paradox” in marketing literature. Second, it expands the applicability of emotions as social information (EASI) theory by empirically validating its explanatory power in visually dominant contexts for the first time. It elucidates how visual complexity stimulates deep emotional resonance via the central route while achieving cognitive efficiency through the peripheral route, thereby providing a novel paradigm for multimodal emotional propagation research. Finally, it systematically introduces cue utilization theory from the domain of commercial decision-making into the context of city marketing. This addresses the practical dilemma faced by city marketing organizations on social media, where narrative depth and dissemination breadth often conflict.