An evaluation method of scientific research team influence based on heterogeneity and node similarity of content and str
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ORIGINAL RESEARCH
An evaluation method of scientific research team influence based on heterogeneity and node similarity of content and structure Zhao Wenbin1 · Fan Tongrang1 · Yin Zhixian2 · Fu Zijian1 · Wu Feng3 Received: 7 May 2019 / Accepted: 13 October 2019 © Springer-Verlag GmbH Germany, part of Springer Nature 2019
Abstract Science research has general rules of development, is like any other social activity. With the improvement of science and technology, scientific problems have become more complex and systematic, individual approach has been replaced by teamwork in scientific research. This paper takes scientific research team cooperative network as research object, analyzes the influence of scientific research teams in the cooperative network from the aspect of node heterogeneity and node similarity of content and structure, and puts forward the influence evaluation method of scientific research team. A scientific research team cooperation network is constructed as the unweighted and undirected graph by the cooperation relationship data of scientific research teams, including co-author, citation, project cooperation and son on. In this network, the scientific research teams are take nodes, and the cooperative relationships between scientific research teams are take as edges. The major factors of scientific research team influence are analyzed, including node heterogeneity and relationship strength between nodes, then a weight and attributed graph is constructed by the research direction of scientific research team and is weighted based on the similarity of nodes’ content and structure by the SimRank model and the Jaccard similarity method. An influence evaluation method was proposed based on the impact of node subjective heterogeneity and node domain heterogeneity, and An influence spread model based on SIR model was given for verifying the proposed influence evaluation method. Keywords Influence evaluation · Scientific research team · Cooperation network · Heterogeneity · Node similarity
1 Introduction
* Fan Tongrang [email protected] Zhao Wenbin [email protected] Yin Zhixian [email protected] Fu Zijian [email protected] Wu Feng [email protected] 1
School of Information Science and Technology, Shijiazhuang Tiedao University, Shijiazhuang, Hebei, China
2
School of Electronics and Information Engineering, Hebei University of Technology, Tianjin, China
3
Institute of Scientific and Technical Information of Heibei Province, Shijiazhuang, Hebei, China
The rapid development of science and technology has prompted researchers’ activities to become increasingly cooperative. In the early days, research methods for research cooperation networks are relatively simple, and only a few simple indictors are used to analyze scientific research cooperation. With the rise of the theory of complex network, Newman (2001a, b, c) used the data of scientific research papers in the fields of physics, biomedicine and computer science to construct a corresponding cooperation network. From the perspective of net
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