Abstract
This study introduces computer vision models for image analysis in advertising research. It reviews the literature in social science and computer science and identifies three categories and nine types of image analysis. The study uses these categories and types as a framework to select 12 computer vision models and compare them on their capability, accuracy, availability, and usability. Nine models are single-functional models, and three are multi-functional models; all 12 have been used in advertising research. The study also demonstrates how two models are used to classify a sample of image ads and assess the aesthetic scores of these ads to answer the research question about the relationship between content categories and aesthetic scores in image ads. It outlines several key steps for the use of computer vision models in advertising research and proposes future research directions. The study can serve as a guide to advertising researchers.
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