CiteSpaceⅡ：科学文献中新趋势与新动态的识别与可视化  

CiteSpace Ⅱ ： Detecting and Visualizing Emerging Trends and Transient Patterns in Scientific Literature

作　　者：陈超美（著）[1] 陈悦（译）[2,3] 侯剑华（译）[2] 梁永霞（译）[2] 

机构地区：[1]Drexel大学信息科学与技术学院,美国费城 [2]大连理工大学21世纪发展研究中心WISE实验室,大连116024 [3]浙江大学公共管理学院,杭州310027

出　　处：《情报学报》2009年第3期401-421,共21页Journal of the China Society for Scientific and Technical Information

摘　　要：本文介绍了在科学文献中识别并显示科学发展新趋势和新动态的一种通用方法的最新研究进展。这项研究在理论和方法上极大地促进了知识领域可视化研究。研究领域（specialty）的概念和可视化基于信息科学中的两个概念——＂研究前沿＂和＂知识基础＂间的时变对偶（time-variant duality）。研究前沿（research front）被定义为一组突现的动态概念和潜在的研究问题。研究前沿的知识基础（intellecture base）是它在科学文献中（即由引用研究前沿术语的科学文献所形成的演化网络）的引文和共引轨迹。Kleinberg设计的跳跃检测算法（burst detection algorithm）适用于辨认新兴研究前沿专业术语概念。Freeman提出的中间中心性测度可以用来使表示潜在范式变化的关键点凸显出来。我们设计并实现了两个互补的视图：聚类视图（cluster views）和时区视图（time-zone views）。这种方法的贡献在于：①通过对研究前沿术语的算法运算,在动态中认识知识基础的本质 ②用研究前沿专业术语概念明确标出共引聚类的确切含义 ③直观地和靠算法识别的关键点的一致性大大简化了可视化的复杂性。CiteSpaceⅡ应用Java程序实现了大规模生物集群灭绝（mass extinction）（1981～2004年）和恐怖主义（terrorism）（1990～2003年）两个研究领域的建模和可视化过程。可视化网络中的突出的趋势和关键点的作用经各自领域专家直接验证,这些专家本身就是关键点文章的的作者。本文讨论了这项研究的实际意义,并明确了今后研究工作中存在的一系列挑战和机会。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 timevariant 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） burstdetection algorithm is adapted tO identify emergent research-front concepts. Freeman＇s （1979） betweenness centrality mettle is used to highlight potential pivotal points of paradigm shift over time. Two complementary visualization views are designed and implemented ： cluster views and time-zone views. The contributions of the approach are that （1）the nature of an intellectual base is algorithmically and temporally identified by emergent research-front terms, （2）the value of a co-citation cluster is explicitly interpreted in terms of research-front concepts, and （3）visually prominent and algorithmieally detected pivotal points substantially reduce the complexity of a visualized network. The modeling and visualization process is implemented in CiteSpaee Ⅱ , a Java application, and applied to the analysis of two research fields： mass extinction （1981 -2004） and terrorism （1990-2003）. Prominent trends and pivotal points in visualized networks were verified in collaboration with domain experts, who are the authors of pivotal-point articles. Practical implications of the work are discussed. A number of challenges and opportunities for future studies are identified. Keywords CiteSpace, information visualization, science f

关 键 词：CITESPACE 信息可视化 科学前沿图谱 知识传播 

分 类 号：G350[文化科学—情报学] TP391.41[自动化与计算机技术—计算机应用技术]