Why did Buddhist institutions fight other Buddhist institutions in pre-modern Japan? Like other instances of religious violence, this phenomenon is hard to understand with any intellectual approach but is especially difficult from an empirical perspective.
Conventionally, attempts to understand this and similar situations have relied on human collection and interpretation of a vast amount of data. Machine learning tools make this process more efficient and accurate but are constrained by the need to have data in a clean, monolithic format. In actuality, the information relevant to religious violence exists in a much more complex, relational format.
Alex Pape and Emily Thomas created a new model that uses both the traditional data-driven methods used by data scientists and the contextual narratives used by humanities scholars to better model and understand complex social phenomena.
Alex Pape is a MS student in the Department of Systems and Information Engineering. He is interested in identifying and developing means of data-driven analysis that are more relevant to socially oriented problems.
Emily Thomas is a MA student in East Asian Studies. Her research focuses on religious violence, specifically in pre-modern Japan.
