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Tracing the evolution of specific topics is a subject area which belongs to the general problem of mapping the structure of scientific knowledge. Often bibliometric data bases are used to study the history of scientific topic evolution from its appearance to its extinction or merger with other topics. In this chapter the authors present an analysis of the academic response to the disaster that occurred in 1986 in Chornobyl (Chernobyl), Ukraine, considered as one of the most devastating nuclear power plant accidents in history. Using a bibliographic database the distributions of Chornobyl-related papers in different scientific fields are analysed, as are their growth rates and properties of co-authorship networks. Elements of descriptive statistics and tools of complex-network theory are used to highlight interdisciplinary as well as international effects. In particular, tools of complex-network science enable information visualization complemented by further quantitative analysis. A further goal of the chapter is to provide a simple pedagogical introduction to the application of complex-network analysis for visual data representation and interdisciplinary communication.
We analyze the reaction of academic communities to a particular urgent topic which abruptly arises as a scientific problem. To this end, we have chosen the disaster that occurred in 1986 in Chornobyl (Chernobyl), Ukraine, considered as one of the mos
Novelty is an inherent part of innovations and discoveries. Such processes may be considered as an appearance of new ideas or as an emergence of atypical connections between the existing ones. The importance of such connections hints for investigatio
There is demand from science funders, industry, and the public that science should become more risk-taking, more out-of-the-box, and more interdisciplinary. Is it possible to tell how interdisciplinary and out-of-the-box scientific papers are, or whi
To quantify the mechanism of a complex network growth we focus on the network of citations of scientific papers and use a combination of the theoretical and experimental tools to uncover microscopic details of this network growth. Namely, we develop
Modern scientific research has become largely a cooperative activity in the Internet age. We build a simulation model to understand the population-level creativity based on the heuristic ant colony algorithm. Each researcher has two heuristic paramet