Data from: Measuring researchers’ potential scholarly impact with structural variations: four types of researchers in information science (1979–2018)
Yang, Xiucai; Hou, Jianhua; Chen, Chaomei (2020), Data from: Measuring researchers’ potential scholarly impact with structural variations: four types of researchers in information science (1979–2018), Dryad, Dataset, https://doi.org/10.5061/dryad.cz8w9gj0w
We propose a method to measure the potential scholarly impact of researchers based on network structural variations they introduced to the underlying author co-citation network of their field. We applied the method to the information science field based on 91,978 papers published between 1979 and 2018 from the Web of Science. We divided the entire period into eight consecutive intervals and measured structural variation change rates (DM) of individual authors in corresponding author co-citation networks. Four types of researchers are identified in terms of temporal dynamics of their potential scholarly impact—1) Increasing, 2) Decreasing, 3) Sustained, and 4) Transient. The study contributes to the understanding of how researchers’ scholarly impact might evolve in a broad context of the corresponding research community. Specifically, this study illustrated a crucial role played by structural variation metrics in measuring and explaining the potential scholarly impact of a researcher. This method based on the structural variation analysis offers a theoretical framework and a practical platform to analyze the potential scholarly impact of researchers and their specific contributions.