Measuring the Cause and Effect in Scientific Productivity: A Case Study of the ACL Community

Causality aims to connect the dots between cause and effect beyond a simple correlation. We rely on the causal analysis as a tool to describe research influences and trends in the computational linguistics (CL) community. Specifically, aiming to draw connections about research productivity based on a scientists’ research portfolio in the area of CL. Studying these research trends is a valuable way to gain insights on a particular discipline and explain research dynamics within and across fields.