A not uncommon desire in digital philosophy-of-science work is to take the measure of a concept or idea and its changing use and meaning over time. How and where has it been invoked? With what has it been related, and in what contexts? This is a natural extension of the kind of classic conceptual analysis often performed by the close reading of a small number of scientific texts, but now with the possibility for us to consider a much wider variety of contexts and authors who may have engaged with an idea. An obvious tool, in turn, for this kind of work is topic modeling, which can be interpreted as dividing a corpus up into the “themes” from which it is constructed. Tracing a term across these “themes” could, then, give us the “semantic neighborhood” surrounding a key term. In which contexts have scientists made reference to terms like “force” or “fitness”? Carefully applied, we could watch the ways in which these neighborhoods change across a corpus or over time. In this talk, I’ll present and evaluate a number of efforts in this direction from my own research: successes and failures in a number of attempts to use topic models, supplemented with various kinds of other information or further complexity, to better understand the cartography of concepts in historical and contemporary philosophy of science. I hope to offer both some fruitful examples and some terrible warnings, in pursuit of some “best practices” for this kind of work.
Charles H. Pence is Chargé de cours (Associate Professor) at the Institut supérieur de philosophie, and Director of the Center for the Philosophy of Science and Society (CEFISES) at the Université catholique de Louvain, Belgium. Previously, he was Assistant Professor and Director of the LSU Ethics Institute at Louisiana State University. Pence received his PhD in History and Philosophy of Science at the University of Notre Dame and BA in Philosophy at Princeton University. He is the author of two books and over twenty articles and book chapters on the philosophy and history of evolutionary theory. His work centres on the integrated philosophy and history of biology, with a particular focus on the introduction and contemporary use of concepts of chance and methods of statistics in evolutionary theory.