Abstract

This paper examines one of the historical antecedents of Big Data, the social physics movement. Its origins are in the scientific revolution of the 17th century in Western Europe. But it is not named as such until the middle of the 19th century, and not formally institutionalized until another hundred years later when it is associated with work by George Zipf and John Stewart. Social physics is marked by the belief that large-scale statistical measurement of social variables reveals underlying relational patterns that can be explained by theories and laws found in natural science, and physics in particular. This larger epistemological position is known as monism, the idea that there is only one set of principles that applies to the explanation of both natural and social worlds. Social physics entered geography through the work of the mid-20th-century geographer William Warntz, who developed his own spatial version called “macrogeography.” It involved the computation of large data sets, made ever easier with the contemporaneous development of the computer, joined with the gravitational potential model. Our argument is that Warntz's concerns with numeracy, large data sets, machine-based computing power, relatively simple mathematical formulas drawn from natural science, and an isomorphism between natural and social worlds became grounds on which Big Data later staked its claim to knowledge; it is a past that has not yet passed.