Abstract
This article discusses promising avenues for integrating affective computational approaches into advertising research on emotion. We review affective computing methods for different modalities—text, visual, and audio—and present advertising research examples and computational tools for each modality. We discuss different state-of-the-art multimodal tools for emotion recognition and propose an evaluation framework for advertising researchers to compare and select appropriate affective computing models. Finally, we discuss how affective computing approaches may fill some research gaps to advance emotion-based advertising research and theory building. This paper contributes theoretical insights, ethical considerations, and practical guidelines essential for the methodological advancement of the emerging field of computational advertising research.
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