Dynamic patterns of open review process

Abstract

Abstract Recently, the open review process has attracted the attention of more and more researchers. In order to deeply and quantitatively understand the process, we employ statistical analysis methods, combining human dynamics theory with the assortative mixing analysis of networks to study the process. Our results present the burst characteristics and preference characteristics of authors and reviewers during the review process. Simultaneously, these results demonstrate the irrelevance between the popularity of the manuscript research topic and the manuscript acceptance rate. Moreover, using the assortative mixing analysis method confirmed that the keywords network basically has obvious assortativity. Furthermore, these results suggest that although no inevitable connection between keywords and the acceptance rate of the manuscript, the combination of keywords in the manuscript is influential. Our research results provide useful points for the design of the review system and paper submission. Future work should analyze more data from other disciplines or deconstruct the underlying mechanism of the open review process.