【作者】 张琳；

【导师】 梁立明；

【作者基本信息】 大连理工大学 ， 管理科学与工程， 2010， 博士

【摘要】 科学结构研究是科学学、科学技术管理以及信息科学等领域的一个重要研究课题。本文基于互引分析、聚类分析和可视化技术等方法,对科学的内在结构进行了量化解读,研究和展现了自然科学与人文社会科学的整体知识结构、信息流动特征与规律。首先,基于“论文-论文”的引用关系,建构了Web of Science (2002-2006)近万种期刊的互引全矩阵作为科学结构研究的基础。提出和设计了“引文强链接”、“引文熵”等一系列计量指标测度科学领域的信息流动特征与规律,为更好地研究科学的内部结构提供了一些新的方法与视角。基于不同的指标,对学术期刊和学科的孤立度、中心性、引文链接分布广度等特征进行了全面的描述和解读。发现了“强链接”较多的期刊与“高引文熵”期刊之间界限分明,人文社会科学领域的学科倾向于扩展其链接分布,而自然科学的学科则更易于拥有较多的强链接等一系列科学结构特征。第二,应用引文聚类和“引文-文本”混合聚类方法对Web of Science中8305种期刊以及约250个学科进行聚类研究,分别得到22个期刊聚类、15个期刊聚类和7个期刊聚类,以及7个ISI学科聚类体系。进一步将得到的聚类结果与传统的“专家”期刊分类体系进行比较研究,将二者结构的一致部分定义为“学科内核”,其余部分则为“学科外围”。所有学科内核形成了科学结构之网的网上纽结,展示了科学知识的差异和学科的多样性。学科外围则展现了学科的分化、交叉、融合、方法的移植以及理论学科和应用学科的相互作用等结构特征。例如,SOOI体系中的“神经科学与行为科学”趋于分化为两个分别具有自然科学倾向和社会科学倾向的聚类,ESI体系中的“心理学”趋于分化为认知心理学和医学心理学两个聚类,而“地理科学”和“空间科学”则显示了较强的交叉融合趋势,数学等基础学科也在不同的学科领域中由于“理论-应用”关系而显示了紧密相连的结构特征。第三,基于引文分析和可视化技术,绘制了一幅包含自然科学、社会科学和人文艺术科学信息交流特征的科学全景图。描绘了自然科学和社会科学不同学科之间交织融合和彼此渗透的现象,展示了现代科学横向交叉渗透、纵向层层相依,在高度分化、高度专门化基础上的高度综合、高度整体化特征,从量化的角度印证了马克思和钱学森关于科学统一趋势的前瞻性理论。在这个科学大统一的“潮流”中,与技术科学紧密相关的“工程学”发挥了重要的沟通作用。此外,通过对不同研究领域,例如声学研究和心理学研究交界面的信息流动特征进行分析,揭示了不同学科之间新的“生长点”,为预测新兴交叉学科的发展提供了参考依据。更多还原

【Abstract】 The study of science structure is an import topic among the fields of science of science, management of science and technology, information science etc. Based on cross-citation analysis, clustering analysis and visualization technology, the whole knowledge structure and the information flow characteristics of natural science, social science and arts & humanity are quantitatively analyzed and presented.Firstly, on the basis of the cross-citation of "paper to paper", a huge cross-citation matrix of some 10,000 journals covered by Web of Science (2002-2006) is constructed. The analyses of science structure is based on this cross-citation matrix. A well-defined set of structure indicators including "strong links", "citation entropy" is proposed and designed for measuring the information flow characteristics, which provide some new methods and visual angles for better understanding of the internal structure of science. Based on different indicators, the degree of isolation, centrality, distribution of citation links of individual journal and subject in the communication network are analyzed and described. Some interesting characteristics of science structure are detected. For instance, there is clear divergence between journals having more "strong links" and those with "high-entropy"; subjects in social science and arts & humanity tend to distribute their links to a far-ranging scope, while subjects within natural science have more strong links.Secondly, a citation-based and a hybrid citation-text-based method are used to cluster 8305 journals and ISI 250 subject categories, respectively results in 22,15 and 7 journal clustering schemes, and 7 subject clusters. Some existing "expert" journal classification systems have been compared with the clustering structure, where the "coincidence" of the two schemes is defined as "subject cores", and the "difference" is "subject peripheries". All the subject cores form the nodes of science structure network, presenting the divergence of knowledge and the diversity of subjects. The subject peripheries present the trend of subject splitting, inter-crossing, convergence, method transplantation, and the interaction between theoretic subjects and applied subjects. For instance, "Neuroscience & behaviour" tend to split into two clusters, respectively with natural science and social science research preference. "Psychology/Psychiatry" in ESI tend to split into cognitive psychology and medical psychology clusters, while "Geosciences" and "Space science" tend to integrate into one cluster. Some theoretical subjects including mathematics have strong affinities with other subjects based on the "theory-application" relationship.Thirdly, based on citation analysis and visualization techniques, a global map of information flow characteristics in science, social science and art & humanities is generated. The information flow among different subjects reveals the intersection, convergence and unification trend of science and social science. The highly integration and unification of science is based on the highly specialities and differentiation. The theories of the unification trend of science proposed by Karl Marx and Qian Xuesen have been proved from the perspective of quantitative analysis. In the whole unification trend of science, "engineering", which is closely related to technological sciences serves as import communication roles. Furthermore, using some information exchange analysis between different subjects, for instance, between "sound" study and "psychology" study, some new growing points and underlying emergence of new inter-disciplines could be detected and revealed.更多还原