Literature DB >> 33816835

Skill ranking of researchers via hypergraph.

Xiangjie Kong1, Lei Liu1, Shuo Yu1, Andong Yang1, Xiaomei Bai2, Bo Xu1.   

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. ©2019 Kong et al.

Entities:  

Keywords:  Hypergraph model; Researcher evaluation; Skill ranking

Year:  2019        PMID: 33816835      PMCID: PMC7924507          DOI: 10.7717/peerj-cs.182

Source DB:  PubMed          Journal:  PeerJ Comput Sci        ISSN: 2376-5992


  13 in total

1.  Adaptive hypergraph learning and its application in image classification.

Authors:  Jun Yu; Dacheng Tao; Meng Wang
Journal:  IEEE Trans Image Process       Date:  2012-03-06       Impact factor: 10.856

2.  Quantifying coauthor contributions.

Authors:  Cagan H Sekercioglu
Journal:  Science       Date:  2008-10-17       Impact factor: 47.728

3.  Quantifying the evolution of individual scientific impact.

Authors:  Roberta Sinatra; Dashun Wang; Pierre Deville; Chaoming Song; Albert-László Barabási
Journal:  Science       Date:  2016-11-04       Impact factor: 47.728

4.  Principles of scientific research team formation and evolution.

Authors:  Staša Milojević
Journal:  Proc Natl Acad Sci U S A       Date:  2014-03-03       Impact factor: 11.205

5.  Enhancing Team Composition in Professional Networks: Problem Definitions and Fast Solutions.

Authors:  Liangyue Li; Hanghang Tong; Nan Cao; Kate Ehrlich; Yu-Ru Lin; Norbou Buchler
Journal:  IEEE Trans Knowl Data Eng       Date:  2016-11-29       Impact factor: 6.977

6.  An absolute index (Ab-index) to measure a researcher's useful contributions and productivity.

Authors:  Akshaya Kumar Biswal
Journal:  PLoS One       Date:  2013-12-31       Impact factor: 3.240

7.  Skill networks and measures of complex human capital.

Authors:  Katharine A Anderson
Journal:  Proc Natl Acad Sci U S A       Date:  2017-11-13       Impact factor: 11.205

8.  Does Interdisciplinary Research Lead to Higher Citation Impact? The Different Effect of Proximal and Distal Interdisciplinarity.

Authors:  Alfredo Yegros-Yegros; Ismael Rafols; Pablo D'Este
Journal:  PLoS One       Date:  2015-08-12       Impact factor: 3.240

9.  Exploiting Publication Contents and Collaboration Networks for Collaborator Recommendation.

Authors:  Xiangjie Kong; Huizhen Jiang; Zhuo Yang; Zhenzhen Xu; Feng Xia; Amr Tolba
Journal:  PLoS One       Date:  2016-02-05       Impact factor: 3.240

10.  Authorship and contribution disclosures.

Authors:  Henry Sauermann; Carolin Haeussler
Journal:  Sci Adv       Date:  2017-11-08       Impact factor: 14.136

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