Skip to the main content

Original scientific paper

https://doi.org/10.17559/TV-20150314110749

Node importance measure for scientific research collaboration from hypernetwork perspective

Quan Xiao ; (1) School of Information Technology, Jiangxi University of Finance and Economics; (2) Jiangxi Key Laboratory of Data and Knowledge Engineering, Yuping West Street 556#, (Mailuyuan District), Nanchang, Jiangxi, China, 330032


Full text: croatian pdf 910 Kb

page 397-404

downloads: 380

cite

Full text: english pdf 910 Kb

page 397-404

downloads: 685

cite


Abstract

Collaboration has become main stream and trend in interdisciplinary fields. In research collaboration organizations, to evaluate the contributions of researchers to the organization and then to identify core researchers is an important issue to carry out performance appraisal and crisis management of brain drain. Scientific research collaboration network is a basic model to investigate this question, but under the context of increasingly complex collaborative behaviour, it shows its limitations for semantic representations. In this paper, by introducing hypernetwork, a more powerful modelling tool than traditional network, and taking scientific paper co-authorship as object to construct scientific research collaboration hypernetwork (SRCH), we measure the importance of researchers in two aspects, as collaborative relationship structure and collaborative achievement value from a hypernetwork perspective. An additive weighting method with adjustable parameters is utilized to integrate the evaluation indicators of the two aspects, and then the synthetical importance evaluation of researchers is obtained. Analysis of data instance verifies that our node importance measure for scientific research collaboration from hypernetwork perspective is reasonable and effective.

Keywords

adjustable parameter; hyper network; node importance; scientific research collaboration network

Hrčak ID:

156828

URI

https://hrcak.srce.hr/156828

Publication date:

27.4.2016.

Article data in other languages: croatian

Visits: 2.410 *