Art and complexity in the era of big data

Abstract

With the advent of large-scale data and the concurrent development of robust scientific tools with which to analyze them, important discoveries are being made in a wider range of scientific disciplines than ever before. Research fields that have gained substantial attention recently include the analytical, large-scale study of human behavior, where many analytical and statistical techniques are applied to various behavioral data from online social media, markets, and mobile communication, enabling meaningful strides in understanding the complex patterns of humans and their social actions. The importance of such research originates from the social nature of humans, an essential human nature that clearly needs to be understood to ultimately understand ourselves. Another ubiquitous essential human nature is that they are creative beings, continually expressing inspirations or emotions in various physical forms such as picture, sound, and writing. As we are successfully probing the social behaviors of humans through science and novel data, it appears increasingly necessary and enlightening to pursue an understanding of the creative nature of humans in an analogous way. Painting, specifically, has played a major role in human expression and creativity. A symbolic process that precedes writing, painting has developed subject to an interplay involving representational conventions and social processes. Our study represents an effort to understand such interactive process by analyzing large-scale digital scans of paintings via a scientific and statistical methodology for quantitatively characterizing the organizing principles of paintings.