Loss of sustainability in scientific work
arXiv:2202.01505 · doi:10.1088/1367-2630/ac6ca1
Abstract
For decades the number of scientific publications has been rapidly increasing, effectively out-dating knowledge at a tremendous rate. Only few scientific milestones remain relevant and continuously attract citations. Here we quantify how long scientific work remains being utilized, how long it takes before today's work is forgotten, and how milestone papers differ from those forgotten. To answer these questions, we study the complete temporal citation network of all American Physical Society journals. We quantify the probability of attracting citations for individual publications based on age and the number of citations they have received in the past. We capture both aspects, the forgetting and the tendency to cite already popular works, in a microscopic generative model for the dynamics of scientific citation networks. We find that the probability of citing a specific paper declines with age as a power law with an exponent of . Whenever a paper in its early years can be characterized by a scaling exponent above a critical value, , the paper is likely to become "ever-lasting". We validate the model with out-of-sample predictions, with an accuracy of up to 90% (AUC ). The model also allows us to estimate an expected citation landscape of the future, predicting that 95% of papers cited in 2050 have yet to be published. The exponential growth of articles, combined with a power-law type of forgetting and papers receiving fewer and fewer citations on average, suggests a worrying tendency toward information overload and raises concerns about scientific publishing's long-term sustainability.
arXiv comment11 pages, 4 figures
References in corpus (25)
- Emergence of scaling in random networks
- Statistical mechanics of complex networks
- The structure and function of complex networks
- Evolution of networks
- Clustering and preferential attachment in growing networks
- How Popular is Your Paper? An Empirical Study of the Citation Distribution
- Quantifying Long-Term Scientific Impact
- Organization of Growing Random Networks
- Measuring preferential attachment for evolving networks
- Evolution of reference networks with aging
- Defining and identifying Sleeping Beauties in science
- Citation Statistics from 110 Years of Physical Review
- Preferential attachment in the growth of social networks: the case of Wikipedia
- The Simultaneous Evolution of Author and Paper Networks
- The first-mover advantage in scientific publication
- Topology and Evolution of Technology Innovation Networks
- Coauthorship and citation in scientific publishing
- Prediction of highly cited papers
- Growing complex network of citations of scientific papers -- measurements and modeling
- The role of mainstreamness and interdisciplinarity for the relevance of scientific papers
- Fractional Dynamics of Network Growth Constrained by aging Node Interactions
- Fame and Obsolescence: Disentangling growth and ageing dynamics of patent citations
- The Time Dimension of Science: Connecting the Past to the Future
- Unraveling the dynamics of growth, aging and inflation for citations to scientific articles from specific research fields
- Life, Death and Preferential Attachment