  This study aims to explore the complex relationship between perceptual and
cognitive interactions in multimodal data analysis,with a specific emphasis on
spatial experience design in overseas Chinese gardens. It is found that
evaluation content and images on social media can reflect individuals' concerns
and sentiment responses, providing a rich data base for cognitive research that
contains both sentimental and image-based cognitive information. Leveraging
deep learning techniques, we analyze textual and visual data from social media,
thereby unveiling the relationship between people's perceptions and sentiment
cognition within the context of overseas Chinese gardens. In addition, our
study introduces a multi-agent system (MAS)alongside AI agents. Each agent
explores the laws of aesthetic cognition through chat scene simulation combined
with web search. This study goes beyond the traditional approach of translating
perceptions into sentiment scores, allowing for an extension of the research
methodology in terms of directly analyzing texts and digging deeper into
opinion data. This study provides new perspectives for understanding aesthetic
experience and its impact on architecture and landscape design across diverse
cultural contexts, which is an essential contribution to the field of cultural
communication and aesthetic understanding.
