Skill ranking of researchers via hypergraph
- Published
- Accepted
- Subject Areas
- Algorithms and Analysis of Algorithms, Computer Architecture, Social Computing
- Keywords
- hypergraph model, skill ranking, researcher evaluation
- Copyright
- © 2019 Kong et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2019. Skill ranking of researchers via hypergraph. PeerJ Preprints 7:e27480v1 https://doi.org/10.7287/peerj.preprints.27480v1
Abstract
Researchers use various skills in their work, such as writing, data analyzing and experiments design. These research skills have greatly influenced quality of their research outputs, as well as their scientific impact. Although there are many indicators having been proposed to quantify the impact of researchers, studies of evaluating their scientific research skills are very rare. In this paper, we analyze the factors affecting researchers' skill ranking and propose a new model based on hypergraph theory to evaluate the scientific research skills. To validate our skill ranking model, we perform experiments on PLoS One dataset and compare the rank of researchers' skills with their papers citation counts and h-index. Finally, we analyze the patterns about how researchers' skill ranking increased over time. Our studies also show the change patterns of researchers between different skills.
Author Comment
This is a submission to PeerJ Computer Science for review.