Dynamic credit allocation in scientific literature

Collaboration among researchers is an essential component of the scientific process, playing a particularly important role in findings with significant impact. While extensive efforts have been devoted to quantifying and predicting scientific impact, the question of how credit is allocated to coauthors of publications with multiple authors within a complex evolving system remains a long-standing problem in scientometrics. In this paper, we propose a dynamic credit allocation algorithm that captures the coauthors’ contribution to a publication as perceived by the scientific community, incorporating a reinforcement mechanism and a power-law temporal relaxation function. The citation data from American Physical Society are used to validate our method. We find that the proposed method can significantly outperform the state-of-the-art method in identifying the authors of Nobel-winning papers that are credited for the discovery, independent of their positions in the author list. Furthermore, the proposed methodology also allows us to determine the temporal evolution of credit between coauthors. Finally, the predictive power of our method can be further improved by incorporating the author list prior appropriately.