Dissecting Landscape Art History with Information Theory

Citation#

Lee, Byunghwee, Min Kyung Seo, Daniel Kim, In-seob Shin, Maximilian Schich, Hawoong Jeong, and Seung Kee Han. 2020. Dissecting landscape art history with information theory. Proceedings of the National Academy of Sciences 117(43): 26580-26590.

Overview#

This paper uses information-theoretic methods to study long-term changes in the composition of landscape paintings. It is one of the central examples of my work at the intersection of data science, art history, and cultural analytics.

Why I Think It Matters#

• It shows how quantitative methods can reveal broad patterns in visual culture
• It bridges physics-inspired methods with art historical questions
• It helped establish a line of work on computational art history in my research

Related#

• Research updates and recognition