Speaker
Description
This study investigates how visual modality is constructed in award-winning tourism images through an AI-augmented multimodal discourse analysis. Drawing on Multimodal Discourse Analysis (Kress & van Leeuwen, 2006) and the interpersonal metafunction in Systemic Functional Linguistics, the study examines how four key visual features—color, lighting, composition, and visual interaction—function as interacting modality markers. A dataset of 20 award-winning photographs was analyzed using a two-stage approach combining AI-driven feature extraction and researcher-led interpretation. The findings reveal that visual modality does not result from individual features but emerges from their interaction, with lighting acting as a primary regulator of realism and stylization, and composition guiding visual salience and viewer attention. Award-winning images consistently demonstrate a balance between authenticity and aesthetic enhancement, suggesting that visual excellence is achieved through multimodal coherence. The study also highlights the role of AI literacy in interpreting AI-generated outputs, emphasizing that while AI enables structured and scalable analysis, meaningful interpretation requires critical human engagement. These findings contribute to multimodal discourse analysis and offer implications for AI-supported approaches to discourse and visual literacy.
