Title
Skill ranking of researchers via hypergraph.
Abstract
Researchers use various skills in their works, such as writing, data analysis and experiments design. These research skills have greatly influenced the quality of their research outputs, as well as their scientific impact. Although many indicators have 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 the 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.
Year
DOI
Venue
2019
10.7717/peerj-cs.182
PEERJ COMPUTER SCIENCE
Keywords
DocType
Volume
Hypergraph model,Skill ranking,Researcher evaluation
Journal
7
ISSN
Citations 
PageRank 
2376-5992
1
0.37
References 
Authors
18
6
Name
Order
Citations
PageRank
Xiangjie Kong142546.56
Lei Liu258864.83
Shuo Yu36813.95
Andong Yang410.37
Xiaomei Bai572.85
Bo Xu630.82