图书情报工作 ›› 2015, Vol. 59 ›› Issue (21): 105-114.DOI: 10.13266/j.issn.0252-3116.2015.21.016

• 情报研究 • 上一篇    下一篇

基于弱共现和突发监测的情报学学科研究主题及交叉性分析

隗玲1,2,3, 许海云1, 郭婷1,2, 方曙1   

  1. 1. 中国科学院成都文献情报中心 成都 610041;
    2. 中国科学院文献情报中心 北京 100190;
    3. 山西财经大学信息管理学院 太原 030006
  • 收稿日期:2015-09-22 修回日期:2015-10-20 出版日期:2015-11-05 发布日期:2015-11-05
  • 作者简介:隗玲(ORCID:0000-0002-0594-3134),博士研究生,E-mail:weiling@mail.las.ac.cn;许海云(ORCID:0000-0002-7453-3331),博士,副研究员;郭婷(ORCID:0000-0002-5072-4045),硕士研究生;方曙(ORCID:0000-0002-4584-7574),研究员,博士生导师,博士。
  • 基金资助:

    本文系国家社会科学青年项目"学科交叉主题识别和预测方法研究"(项目编号:14CTQ033)和中国科学院青年创新促进会基金研究成果之一。

Study on the Interisciplinary Topics of Information Science Based on Weak Co-occurrence and Burst Detecting

Wei Ling1,2,3, Xu Haiyun1, Guo Ting1,2, Fang Shu1   

  1. 1. Chengdu National Science Library, Chinese Academy of Sciences, Chengdu 610041;
    2. National Science Library, Chinese Academy of Sciences, Beijing 100190;
    3. School of Information Management, Shanxi University of Finance and Economics, Taiyuan 030006
  • Received:2015-09-22 Revised:2015-10-20 Online:2015-11-05 Published:2015-11-05

摘要:

[目的/意义]运用弱共现和突发监测两种研究方法,在微观层面对情报学学科的研究主题及其交叉性进行分析,以期揭示与科交叉规律,促进学科交叉研究。[方法/过程]获取情报学学科科研论文的高频主题词,在此基础上生成高频词共现矩阵,并进一步生成弱共现网络,对弱共现网络呈现出的主题及交叉性进行分析。同时,对高频主题词进行突发监测。[结果/结论]研究结果显示,在高频词强共现网络中不突出的研究主题会在高频词弱共现网络凸显出来,这些研究主题可能是当期的研究重点,也可能是将来的研究重点和热点;主题之间弱关系被定义为4类,体现了情报学学科微观层面的交叉性;突发探测结果在研究时间段内显示的研究热点趋势和强共现网络的聚类结果具有一致性,在揭示具有学科交叉性的新研究主题时体现出敏感性、突出性和动态性优势。

关键词: 研究主题, 共现网络, 弱关系, 突发监测, 交叉性

Abstract:

[Purpose/significance]Thkis paper, from a new research perspective, aims to study theinterdisciplinarytopics of information science at the micro level based on weak co-occurrence and burst detecting. [Method/process]High currency terms of information scientific papers were selected, the co-occurrence matrix of which was generated. We used the matrix to get a weak co-occurrence network, and analyzed research topics and their interdisciplinary ones. On the other hand, burst detecting was conducted on the high currency terms.[Result/conclusion]According to the research, the less highlighted topics in the strong co-occurrence network will become obvious in the weak co-occurrence network, which maybe the current focuses or potential focuses. The weak ties between topics can be thoroughly defined into four types, which embody the micro interdisciplinary topics of information science. The burst detecting results show thatthe hotspot trend in the research period is consistent with the clustering of strong co-occurrence network. Burst detecting has a unique advantage to reveal the new interdisciplinary topics sensitively, specifically and dynamically.

Key words: research topics, co-occurrence, weak tie, burst detecting, interdisciplinary

中图分类号: