VISUAL COMMUNICATION STRATEGIES IN DIGITAL CRISIS MANAGEMENT: AN AI-ENABLED MEDIA ANALYSIS APPROACH - Dixit, Deepa; Sharma, Riya Goel; Patil, Mukesh; Ramtirthkar, Chandrashekhar Ramesh; Goel, Pooja; Nagargoje, Yogesh (ShodhKosh: Journal of Visual and Performing Arts, 2025)
This paper examines the visual communication techniques used in crisis management regarding the digital environment with the help of an AI-enhanced media analysis system that allows evaluating the tools of clarity, credibility, and emotional appeal on the platform quickly on the high-velocity. In times of crisis, the visuals that are spread through social media, news portals, and official dashboards have a potent impact in shaping the perception of people and their actions, but the evaluation is rather divided and subjective. This study aims at coming up with a scalable system that will measure the visual effectiveness and compliance with the crisis communication objectives. The given method involves the usage of computer vision, multimodal transformers, and graph-based diffusion modelling, which would be applied to analyze the image, infographics, maps, and video frames and capture and temporal contexts. Models of elements to do with salience, color semantics, iconography, spatial hierarchy, facial affect and uncertainty cues are extracted and combined with signals that relate to engagement and propagation. The performance of strategy is determined through indicators of understanding, credibility, emotional control and risk of misinformation. Multi-crisis Multi-crisis experiments on multi-crisis datasets in the fields of public health, natural disasters and infrastructure failures indicate that the framework is better at detecting misleading visuals, and design of messages, which improve in understanding predictions by up to 18% and anxiety amplifying factors, respectively, over baseline heuristics. Heatmaps and design suggestions are offered to communicators in real-time with the help of interpretable outputs. These results allow concluding that AI-based visual analytics has the potential to positively influence the crisis-related coordination, transparency, and compliance with media members and agencies, providing them with the necessary actions to follow and assisting in the work.