A Novel Approach to Predicting Exceptional Growth in Research
arXiv:2004.13159 · doi:10.1371/journal.pone.0239177
Abstract
The prediction of exceptional or surprising growth in research is an issue with deep roots and few practical solutions. In this study we develop and validate a novel approach to forecasting growth in highly specific research communities. Each research community is represented by a cluster of papers. Multiple indicators were tested, and a composite indicator was created that predicts which research communities will experience exceptional growth over the next three years. The accuracy of this predictor was tested using hundreds of thousands of community-level forecasts and was found to exceed the performance benchmarks established in Intelligence Advanced Research Projects Activity's (IARPA) Foresight Using Scientific Exposition (FUSE) program in six of nine major fields in science. Furthermore, ten of eleven disciplines within the Computing Technologies field met the benchmarks. Specific detailed forecast examples are given and evaluated, and a critical evaluation of the forecasting approach is also provided.
arXiv comment25 pages, 4 figures, 10 tables inline
References in corpus (4)
- Electric Field Effect in Atomically Thin Carbon Films
- From Louvain to Leiden: guaranteeing well-connected communities
- A smart local moving algorithm for large-scale modularity-based community detection
- Which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge?
Cited by in corpus (3)
- The whack-a-mole governance challenge for AI-enabled synthetic biology: literature review and emerging frameworks
- Empirical analysis of recent temporal dynamics of research fields: Annual publications in chemistry and related areas as an example
- Topics Emerged in the Biomedical Field and Their Characteristics