Digital Imprints of Personal Heritage: An AI-Driven Analysis of Image Structure, Color, and Content Across Online Communities

Digital platforms have become primary channels for cultural heritage transmission, yet how individuals visually represent their personal heritage online remains unexplored. This study investigates the visual patterns in personal heritage representation across digital platforms, examining whether platform affordances or demographics influence these patterns. Through the LAVIS multimodal AI system, we analyzed 588 heritage images from Instagram and “Personas y Patrimonios”, combining automated content, composition, color, and saturation analyses with human validation. Our findings revealed that intimate, portable objects—particularly jewelry (22.79%)—dominate personal heritage representations, with no content differences between platforms or genders. Small but statistically significant platform differences emerged in color patterns (Cohen’s d = −0.215) and compositional attention (Cohen’s d = 0.147), while gender showed no significant differences in any visual dimension. These findings may indicate that personal heritage representation follows universal visual patterns, emphasizing personal bonds that transcend both platform affordances and demographic differences. These results advance understanding of personal digital heritage communication by identifying the universal patterns in its visualization. Beyond establishing a methodological framework for AI-assisted heritage image analysis, this research provides practical insights for heritage educators and digital platform designers while illuminating how biographical objects function in digital environments, ultimately underscoring the pivotal role of imagery in contemporary cultural transmission.