Journal of Social Computing


clothing, fashion, weight perception, body size, crowdsourcing


In many societies, appearing slim (corresponding to a small body-mass index) is considered attractive. The fashion industry has been attempting to cater to this trend by designing outfits that can enhance the appearance of slimness. Two anecdotal rules, widespread in the world of fashion, are to choose dark clothes and avoid horizontal stripes, in order to appear slim. Thus far, empirical evidence has been unable to conclusively determine the validity of these rules, and there is consequently much controversy regarding the impact of both color and patterns on the visual perception of weight. In this paper, we aim to close this gap by presenting the results from a series of large-scale crowdsourcing studies that investigate the above two claims. We gathered a dataset of around 1000 images of people from the Web together with their ground-truth weight and height as well as clothing attributes about colors and patterns. To elicit the effects of colors and patterns, we asked crowd workers to estimate the weight in each image. For the analysis, we controlled potential confounds by matching images in pairs where the two images differ with respect to color or pattern, but are similar with respect to other relevant aspects. We created image pairs in two ways: firstly, observationally, i.e., from two real images; and secondly, experimentally, by manipulating the color or pattern of clothing in a real image via photo editing. Based on our analysis, we conclude that dark clothes indeed decrease perceived weight slightly but statistically significantly, and horizontal stripes have no discernible effect compared to solid light-colored clothes. These results contribute to advancing the debate around the effect of specific clothing colors and atterns and thus provide empirical grounds for everyday fashion decisions. oreover, our work gives an outlook on the vast opportunities of using crowd sourcing in the modern fashion industry


Tsinghua University Press