Innovation or imitation: The diffusion of citations

• Published in: Journal of the American Society for Information Science and Technology 2018-10, Vol.69 (10), p.1271-1282
• Main Authors: Min, Chao, Ding, Ying, Li, Jiang, Bu, Yi, Pei, Lei, Sun, Jianjun
• Format: Article
• Language: English
• Subjects: Bibliometrics; Citation analysis; Diffusion; Imitation; Innovations; Life cycle analysis; Life cycle assessment; Life cycle engineering
• ISSN: 2330-1635; 2330-1643
• DOI: 10.1002/asi.24047

Citations in scientific literature are important both for tracking the historical development of scientific ideas and for forecasting research trends. However, the diffusion mechanisms underlying the citation process remain poorly understood, despite the frequent and longstanding use of citation counts for assessment purposes within the scientific community. Here, we extend the study of citation dynamics to a more general diffusion process to understand how citation growth associates with different diffusion patterns. Using a classic diffusion model, we quantify and illustrate specific diffusion mechanisms which have been proven to exert a significant impact on the growth and decay of citation counts. Experiments reveal a positive relation between the “low p and low q” pattern and high scientific impact. A sharp citation peak produced by rapid change of citation counts, however, has a negative effect on future impact. In addition, we have suggested a simple indicator, saturation level, to roughly estimate an individual article's current stage in the life cycle and its potential to attract future attention. The proposed approach can also be extended to higher levels of aggregation (e.g., individual scientists, journals, institutions), providing further insights into the practice of scientific evaluation.