In this project, art historical insights on the qualitative appreciation of specific iconographic and pictorial aspects of paintings are applied to influencers’ visuals on Instagram to discover systematic patterns and insight into the role of visual elements in multimodal communication. The results of this interdisciplinary research will inform researchers of computer vision models to identify visual elements in digital media that attract viewers and explain their preferences. For influencers, artists and users of multimodal platforms in which communication through visual imagery is central, the insights from this research contribute to knowledge about the workability of visual elements and thus to their successful deployment.

In different research fields, visual elements have been found to affect viewer responses. Advertising research shows that the ways in which visual metaphors are portrayed affect viewers’ appreciation. Auction masters developed rules of thumb when valuing paintings: cats higher than dogs; a woman’s portrait higher than a man’s; creatures walking towards you higher than walking away. Analyses of art auctions have shown systematic effects of colours in paintings on their hammer prices. The visual elements that we may identify seem endless, but in Kress and Van Leeuwen (2020) a useful analytic toolbox has been developed (without assumptions about appreciation) to categorize images on the basis of explicitly defined visual features. In this project we want to explore the effects of visual features on the hammer prices of carefully curated corpora of paintings (RQ1), thus revealing specific patterns that may explain social media responses on Influencers’ Instagram posts (RQ2). In this interdisciplinary way, we will make visual contemporary communication insightful and measurable, and contribute to the knowledge about visual communication and the processes underlying global digital platforms like Instagram.

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