Computational Methods

The widespread adoption of computational methods in social sciences can be traced back to at least the 1990s (and much earlier for quantitative-driven disciplines like economics). Computational methods can encompass a broad range of tools, ranging from regression analysis to prediction-based machine learning. The integration of such methods in the social sciences is, in part, a result of the rapid advancements and increased accessibility of both hardware and software. In recent times, there's been a notable uptick in the enthusiasm for digital methods within the humanities. While it may not be necessary for humanities scholars to mimic the exact methodologies of social scientists, particularly their rigorous quest for mathematically proven causality, the real benefit for historians lies in discerning patterns and relationships from vast datasets, which traditional historical methods might find challenging. I am passionate about harnessing Natural Language Processing (NLP) techniques to explore and address historical questions.