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  • Author or Editor: Xia Gao x
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Abstract

This paper introduces a diffusion network model: an individual-citation-based directed network model with a time dimension, as a potentially useful approach to capture the diffusion of research topics. The approach combines social network analysis, network visualization and citation analysis to discuss some of the issues concerning the spread of scientific ideas. The process of knowledge diffusion is traced from a network point of view. Using research on the h-index as a case study, we built detailed networks of individual publications and demonstrated the feasibility of applying the diffusion network model to the spread of a research. The model shows the specific paths and associations of individual papers, and potentially complementing issues raised by epidemic models, which primarily deal with average properties of entire scientific communities. Also, based on the citation-based network, the technique of main path analysis identified the articles that influenced the research for some time and linked them into a research tradition that is the backbone of the h-index field.

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Abstract  

Bioinformatics is an emerging and rapidly evolving discipline. The bioinformatics literature is growing exponentially. This paper aims to provide an integrated bibliometric study of the knowledge base of Chinese research community, based on the bibliometric information in the field of bioinformatics from SCI-Expanded database during the period of 2000–2005. It is found that China is productive in bioinformatics as far as publication activity in international journals is concerned. For comparative purpose, the results are benchmarked against the findings from five other major nations in the field of bioinformatics: USA, UK, Germany, Japan and India. In terms of collaboration profile, the findings imply that the collaborative scope of China has gradually transcended boundaries of organizations, regions and nations as well. Finally, further analyses on the citation share and some surrogate scientometric indicators show that the publications of Chinese authors suffer from a lowest international visibility among the six countries. Strikingly, Japan has achieved most remarkable impact of publication when compared to research effort devoted to bioinformatics amongst the six countries. The policy implication of the findings lies in that Chinese scientific community needs much work on improving the research impact and pays more attention to strengthening the academic linkages between China and worldwide nations, particularly scientifically advanced countries.

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Abstract  

We apply social network analysis to display the characteristics of the networks resulting from bibliographic coupling of journals by the Chinese patent data of United States Patent and Trademark Office (USPTO) between 1995 and 2002. The networks of journals in all fields, the three strongly science-based fields (i.e. Biotechnology, Pharmaceuticals, and Organic Fine Chemistry), and the three weakly science-based fields (i.e. Optics, Telecommunications, and Consumer Electronics), have been analyzed from the global and the ego views, respectively. We study a variety of statistical properties of our networks, including number of actors, number of edges, size of the giant component, density, mean degree, clustering coefficient and the centralization measures of the network. We also highlight some apparent differences in the network structure between the subjects studied. Besides, we use the three centrality measures, i.e. degree, closeness, and betweenness, to identify the important journals in the network of all fields and those strongly science-based networks.

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Abstract

Only a few cases of systematic empirical research have been reported investigating collaborative knowledge production in China and its implications for China's national and regional innovation system. Using Chinese patent data in the US Patent and Trademark Office (USPTO), this paper examines the geographic variations in intraregional, inter-regional and international knowledge exchanges of China from 1985 to 2007. Degree centrality reveals that intraregional and international collaborations are the main channels of knowledge exchange for the provinces and municipalities of China while inter-regional knowledge exchange is relatively weak. Besides, over the two decades, the knowledge exchange network has been expanding (connecting an increasing number of provinces and countries), becoming more decentralized (increasing number of hubs) and more cohesive (more linkages). A blockmodel analysis further reveals that the inter-regional network of China begins to show characteristics of a core-periphery structure. The most active knowledge exchange occurs between members of the core block composed by the most advanced provinces while the members of the peripheral block from less favored regions have few or no local and extra-local knowledge exchange. Building a strong knowledge transfer network would much improve the innovation capacities in less favored regions and help them break out from their “locked-in” development trajectories.

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