| 标题 |
 CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature 相关领域
可视化
中间性中心性
引用
数据科学
计算机科学
领域（数学分析）
信息可视化
中心性
数据挖掘
万维网
数学分析
数学
组合数学
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| DOI |
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| 其它 | This article describes the latest development of a generic approach to detecting and visualizing emerging trends and transient patterns in scientific literature. The work makes substantial theoretical and methodological contributions to progressive knowledge domain visualization. A specialty is conceptualized and visualized as a time-variant duality between two fundamental concepts in information science: research fronts and intellectual bases. A research front is defined as an emergent and transient grouping of concepts and underlying research issues. The intellectual base of a research front is its citation and co-citation footprint in scientific literature—an evolving network of scientific publications cited by research-front concepts. Kleinberg's (2002) burst-detection algorithm is adapted to identify emergent research-front concepts. Freeman's (1979) betweenness centrality metric is used to highlight potential pivotal points of paradigm shift over time. |
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