Get to the top and stay there: A study of citation rank dynamics in academia

Abstract

Citations serve as an important metric for identifying experts and opinion leaders in academic communities. In this paper, we analyze the evolution of yearly rankings of top-cited (C-list) authors in the domain of Computer Science. In searching for factors that help authors become top-cited, we also gather authors in the top-collaboration list (A-list) and top-publication list (P-list) for each year, and analyze cross-correlation of the C-list with the corresponding A-list and P-list for each year. Results show that the A-list and P-list serve as (unreliable) indicators for appearance on the C-list, but their effect is quick and short-lived. Through further case studies we find other key factors, such as the seminal importance of an author's publication and the association on an author's work with hot topic trends, may significantly affect rank dynamics. Based on the study of citation rank dynamics in academia, we then discuss the modeling of rank dynamics, specifically a model based on item visibility and item strength, and the general applicability of such a model.