This paper analyzes 630,000 paintings from 1400 onward to uncover how visual art reflects its socioeconomic context. We develop a learning algorithm to predict nine basic emotions conveyed in each painting and isolate a context effect---the emotional signal shared across artworks created in the same location and year---controlling for artist, genre, and epoch-specific influences. These emotion distributions encode subtle but meaningful information about the living standards, uncertainty, or