Pattern making and pattern breaking

Abstract

How do new ideas emerge in academic contexts and what forces determine which ideas get selected and which are forgotten? We analyze all papers presented at the ANPEC Brazilian Economics National Meetings from 2013 to 2019 using topic modeling and Kullback-Leibler divergence to measure novelty and resonance. In contrast to simply counting citations or reference combinations, these methods explore the Shannon information in the actual texts to detect the rise of new patterns and whether these patterns persist once they have been established. We find that novelty is highly correlated with transience so that most new ideas are quickly forgotten. However, of the ideas that persist, those that are more novel have higher impact. We show that our text-based measure of impact is correlated with subsequent citations.