本文对国际科学计量学杂志《Ｓｃｉｅｎｔｏｍｅｔｒｉｃｓ》１９７９－１９９１年的研究论文内容、栏目、作者及国别和编委及国别作了计量分析，揭示出科学计量学研究的重点、活动的中心及发展趋势，说明了学科带头人在发展科学计量学这门新兴学科中的作用。

国际刊物《Scientometrics》文献计量研究

Scientific collaboration networks are a hallmark of contemporary academic research. Researchers are no longer independent players, but members of teams that bring together complementary skills and multidisciplinary approaches around common goals. Social network analysis and co-authorship networks are increasingly used as powerful tools to assess collaboration trends and to identify leading scientists and organizations. The analysis reveals the social structure of the networks by identifying actors and their connections. This article reviews the method and potential applications of co-authorship network analysis in health. The basic steps for conducting co-authorship studies in health research are described and common network metrics are presented. The application of the method is exemplified by an overview of the global research network for Chikungunya virus vaccines.

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Co-authorship network analysis in health research: method and potential use.

Does country-level R&D efficiency benefit from the collaboration network structure?

Do research institutes benefit from their network positions in research collaboration networks with industries or/and universities?

A model is proposed to study the coevolution of network and knowledge.The network evolves from random to small-world, when knowledge diversity remains.The small-world diminishes with the reduction of knowledge-transfer effectiveness.Strong cohesion can lead to network separation, and reduce long-term transfer. Knowledge diffusion in social networks has extensively been studied in the communities of knowledge and innovation management and of complex networks. However, less attention has been paid on the coevolution of knowledge and network. In this work an agent-based model is proposed to study such coevolutionary dynamics. A set of agents, which are initially interconnected to form a random network, either exchange knowledge with their neighbors or move toward a new location through an edge-rewiring procedure. The activity of knowledge exchange between agents is determined by a knowledge transfer rule that two connecting agents exchange knowledge only if their knowledge distance is less than a given threshold. What's more, within the threshold, knowledge exchange is more effective when the knowledge distance is greater. The activity of agent movement is determined by a neighborhood adjustment rule that one agent may move toward a remote location or reside in the local cluster. Through simulative analysis of this model, some interesting phenomena are observed. Essentially, the bi-directional influences between knowledge transfer and neighborhood adjustment give rise to the coevolution of the network structure and the diffusion of knowledge at the global level. In particular, the rise and fall of "small-world" structure of the network can be observed during the process of knowledge transfer.

A study on coevolutionary dynamics of knowledge diffusion and social network structure

Many of the novel ideas that lead to scientific publications or yield technological advances are the result of collaborations among scientists or inventors. Although various aspects of collaboration networks have been examined, the impact of many network characteristics on knowledge creation and innovation production remains unclear due to the inconsistency of the conclusions from various research studies. One such network structure, called small world, has recently attracted much theoretical attention as it has been suggested that it can enhance the information transmission efficiency among the network actors. However, the existing empirical studies have failed to provide consistent results regarding the effect of small-world network properties on network performance in terms of its scientific and technological productivity. In this paper, using the data on 29 years of journal publications and patents in the field of biotechnology in Canada, the network of scientists' collaboration activities has been constructed based on their co-authorships in scientific articles. Various structural properties of this network have been measured and the relationships between the network structure and knowledge creation, and quantity and quality of technological performance have been examined. We found that the structure of the co-authorship network of Canadian biotechnology scientists has a significant effect on the knowledge and innovation production, but it produced no impact on the quality of patents generated by these scientists.

Hamidreza Eslami

Papers

Effect of collaboration network structure on knowledge creation and technological performance: the case of biotechnology in Canada