Current Volume 9
Narrative-Based Emotional Intelligence: Inferring Psychological States from Image-Elicited User Stories Using Generative AI
Abstract
Conventional sentiment analysis methods primarily depend on direct textual input, which often limits the accurate understanding of deeper psychological states due to controlled or incomplete emotional expression In response to this limitation, the present study introduces a narrative-based emotional intelligence framework that utilizes image-driven storytelling combined with generative artificial intelligence techniques. Within the suggested methodology, participants are exposed to image-based stimuli and asked to describe or narrate the scene in their own words. The collected narratives are processed through computational linguistic techniques and generative AI to identify emotional cues, sentiment patterns, and contextual meanings. The derived findings are subsequently applied to infer psychological indicators such as emotional state, anxiety tendencies, and optimism levels. The system also incorporates temporal analysis to track variations in user responses over time. The key contribution of this work lies in integrating visual prompts with narrative analysis to capture more natural and expressive emotional responses.
Keywords
Emotional Intelligence, Affective Computing, Generative AI, Natural Language Processing, Image Stimuli, Narrative Analysis, Psychological State Detection
Citations
IRE Journals:
Madhura Mukund Rohinkar, Ashwini Garkhedkar "Narrative-Based Emotional Intelligence: Inferring Psychological States from Image-Elicited User Stories Using Generative AI" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 4437-4442 https://doi.org/10.64388/IREV9I11-1718330
IEEE:
Madhura Mukund Rohinkar, Ashwini Garkhedkar
"Narrative-Based Emotional Intelligence: Inferring Psychological States from Image-Elicited User Stories Using Generative AI" Iconic Research And Engineering Journals, 9(11) https://doi.org/10.64388/IREV9I11-1718330
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