当今万维网、社会网等复杂网络规模的迅猛发展,传统的文字和表格形式已无法满足日益庞大的网络数据的分析和管理,而可视化技术作为一种有效的辅助理解复杂网络的结构并从中挖掘有用信息的方法而得到广泛应用.本文以Web of Science数据...当今万维网、社会网等复杂网络规模的迅猛发展,传统的文字和表格形式已无法满足日益庞大的网络数据的分析和管理,而可视化技术作为一种有效的辅助理解复杂网络的结构并从中挖掘有用信息的方法而得到广泛应用.本文以Web of Science数据库中关于复杂网络可视化的文献为研究对象,利用Citespace软件绘制出该领域的相关知识图谱,研究结果直观的展示了该研究领域主要国家、主要机构、核心期刊;揭示了复杂网络可视化研究领域由理论研究到实证研究、方法探索到实际应用的演进路径;指出可视化算法、可视化工具的研究等为热点,社会网络分析、数据挖掘等研究为前沿,为更快、更好的了解复杂网络可视化研究领域基础及研究进展提供有价值的参考.展开更多
Co-word networks are constructed with author-provided keywords in academic publications and their relations of co-occurrence.As special form of scientific knowledge networks,they represent the cognitive structure of s...Co-word networks are constructed with author-provided keywords in academic publications and their relations of co-occurrence.As special form of scientific knowledge networks,they represent the cognitive structure of scientific literature.This paper analyzes the complex structure of a co-word network based on 8,190 author-provided keywords extracted from 3,651 papers in five Chinese core journals in the field of management science.Small-world and scale-free phenomena are found in this network.A large-scale co-word network graph,which consists of one major giant component and many small isolated components,has been generated with the GUESS software.The dynamic growth of keywords and keyword co-occurrence relationships are described with four new informetrics measures.The results indicate that existing concepts always serve as the intellectual base of new ideas as represented by keywords.展开更多
文摘当今万维网、社会网等复杂网络规模的迅猛发展,传统的文字和表格形式已无法满足日益庞大的网络数据的分析和管理,而可视化技术作为一种有效的辅助理解复杂网络的结构并从中挖掘有用信息的方法而得到广泛应用.本文以Web of Science数据库中关于复杂网络可视化的文献为研究对象,利用Citespace软件绘制出该领域的相关知识图谱,研究结果直观的展示了该研究领域主要国家、主要机构、核心期刊;揭示了复杂网络可视化研究领域由理论研究到实证研究、方法探索到实际应用的演进路径;指出可视化算法、可视化工具的研究等为热点,社会网络分析、数据挖掘等研究为前沿,为更快、更好的了解复杂网络可视化研究领域基础及研究进展提供有价值的参考.
基金supported by the National Natural Science Foundation of China(Grant Nos.71003078and 70833005)sponsored by SRF for ROCS and SEM
文摘Co-word networks are constructed with author-provided keywords in academic publications and their relations of co-occurrence.As special form of scientific knowledge networks,they represent the cognitive structure of scientific literature.This paper analyzes the complex structure of a co-word network based on 8,190 author-provided keywords extracted from 3,651 papers in five Chinese core journals in the field of management science.Small-world and scale-free phenomena are found in this network.A large-scale co-word network graph,which consists of one major giant component and many small isolated components,has been generated with the GUESS software.The dynamic growth of keywords and keyword co-occurrence relationships are described with four new informetrics measures.The results indicate that existing concepts always serve as the intellectual base of new ideas as represented by keywords.
