Leadership in scholarship: A machine learning based investigation of editors' influence on textual structure

Academic journals disseminate new knowledge, and editors of prominent journals are in a position to affect the direction and composition of research. Using machine learning procedures, we measure the influence of editors of the American Economic Review (AER) on the relative topic structure of papers published in the AER and other top general interest journals. We apply the topic analysis apparatus to the corpus of all publications in the Top 5 journals in Economics between 1976 and 2013, and also to the publications of the AER's editors during the same period. This enables us to observe the changes occurring over time in the relative frequency of topics covered by the AER and other leading general interest journals over time. We .nd that the assignment of a new editor tends to coincide with a change of topics in the AER in favour of a new editor's topics which can not be explained away by shifts in overall research trends that may be observed in other leading general interest journals.