| 一种基于共词网络社区的科研主题演化分析框架 |
| |
| 引用本文： | 程齐凯,王晓光.一种基于共词网络社区的科研主题演化分析框架[J].图书情报工作,2013,57(8):91-96. |
| |
| 作者姓名： | 程齐凯 王晓光 |
| |
| 作者单位： | 武汉大学信息管理学院 |
| |
| 基金项目： | 国家自然科学基金项目"基于语义共词网络演化的学科新兴趋势浮现机理与探测研究"，中央高校基本科研业务费专项资金资助项目 |
| |
| 摘 要： | 共词网络在一定程度上可以表示特定学科领域的知识结构。为分析主题演化过程,将网络社区的演化分为6种类型,分别为产生、消亡、分裂、合并、扩张与收缩。在此基础上,利用Z-value算法和社区相似度算法,构建一个科研主题演化分析模型。与传统的基于词频的分析思路相比,所提出的基于共词网络社区演化分析的框架不强调词频的变化,而是强调词间关系的变化,试图通过中观层面的网络社区的演化分析揭示科研主题发展规律。
|
| 关 键 词： | 共词网络 网络社区 社区发现 网络演化 新兴趋势探测 |
| 收稿时间： | 2012-11-27 |
A New Research Frame for Analyzing the Evolution of Research Topics Based on Co-word Network Communities |
| |
| Cheng Qikai,Wang Xiaoguang.A New Research Frame for Analyzing the Evolution of Research Topics Based on Co-word Network Communities[J].Library and Information Service,2013,57(8):91-96. |
| |
| Authors: | Cheng Qikai Wang Xiaoguang |
| |
| Institution: | School of Information Management, Wuhan University, Wuhan 430072 |
| |
| Abstract: | The knowledge structure of a discipline can be expressed by a co-word network. Six types of evolution of community are recognized, which are birth, death, splitting, merging, growth, and contraction. A topic evolution analysis framework is created based on Z-value mechanism and community match mechanism. Comparing with the traditional methods, the method proposed in this paper focus on the links between words rather than the frequency of words, which is a innovation in the field of ETD from the mesoscopical network view. |
| |
| Keywords: | Co-word Network Network Communities Community Detection Network Evolution Emerging Trend Detection |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《图书情报工作》浏览原始摘要信息 |
| 点击此处可从《图书情报工作》下载免费的PDF全文 |
|
