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Decoding Viewer Emotions in Visual Media

Neuromarketing Perspectives on Digital Art and Online Visual Advertising

Bibliographic Data

ID22197940
AuthorsArchana Borde (Symbiosis International University), Neelam Raut (Prin. L. N. Welingkar Institute of Management Development and Research), Girdhar Gopal (Indian Institute of Technology BHU), Prashant Kalshetti (0000-0003-3553-2093, Dr. D.Y. Patil Vidyapeeth, Pune), Gaganpreet Kaur Ahluwalia (Savitribai Phule Pune University), Nilesh Anute (0000-0001-6599-813X, Sri Balaji Vidyapeeth University), Shailesh Tripathi (0000-0001-5142-3781, Sri Balaji Vidyapeeth University)
Year2025
Volume6
Issue4s
Pages571-581
Publication date2025-12-25
Open AccessYes
TypeARTICLE
VenueShodhKosh: Journal of Visual and Performing Arts (JOURNAL)
Journal identifiersISSN: 2582-7472 • E-ISSN: 2582-7472
PublisherGranthaalayah Publications and Printers (PUBLISHER • IN)
DOI10.29121/shodhkosh.v6.i4s.2025.6970
OpenAlexW7117717584
LanguageEN
References cited14

The emotional reaction of the viewer to visual media is one of the key issues of digital art and visual advertising online where the aesthetic impression directly determines the attention, memory, and choice. Current methods of evaluation are based on self-reports and superficial measures of engagement which provide little information on underlying affective reactions that underlie consumer behavior. This gap has been filled in this paper by considering viewer emotion decoding in the light of neuromarketing viewpoint that involves applying computational emotion analysis with visual media research. The main goal is to explore the effects of visual characteristics, narrative, and style in digital art and web-based advertisements in order to stimulate measurable emotional response and connect such a response to the results of engagement and persuasion. The paper is a synthesis of results on emotion recognition models, biometric measures, and behavioral analytics to create a hybrid framework of analytical analysis of affect-based visual comparison. The central results have shown that emotion-sensitive visual design is much more efficient in retaining attention, emotional appeal, and brand memorability, as positive affect and moderate arousal become the most prominent predictors of the viewer involvement in any platform. Moreover, the adaptive images in terms of emotions proved to be more effective than the non-adaptive ones in respect of having the artistic meaning and selling messages. The paper has a wider scope than commercial advertising in respect to digital art shows, immersive media and culturally contextual visual storytelling, with an emphasis on ethical aspects and issues on interpretability. This work provides a systematic base of the research on emotionally intelligent visual media and the potential further study of visual communication and neural markers by connecting neuromarketing and visual analytics based on AI and emotion recognition

Appeal to emotion · Decoding methods · Digital media · Eye movement · Eye tracking · Neuromarketing · Perception · Visual rhetoric · Aesthetic Perception and Analysis · Digital Media and Visual Art · Emotion and Mood Recognition

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Highly citedNo

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