Triangulation of history using textual data

This essay describes essential considerations and select methods in computational text analysis for use in the study of history, specifically the history of science and biomedicine. It explores specific approaches that can be used for understanding conceptual change over time in a large corpus of documents. By way of example, using a corpus of 27,977 articles collected on the microbiome, the essay studies the general microbiome discourse for the years from 2001 to 2010, examines the usage and the sense of the word “human” from 2001 to 2010, and highlights shifts in the microbiome discourse from 2001 to 2010.