兼顾中低频关键词的共词分析实践——以图书情报学高被引文章为例

Medium and Low Frequency Keywords in Co-word Analysis: A Case Study of Highly Cited Articles in Library and Information Science

分年度选取了图书情报学高被引论文作为研究样本。指出了高频关键词共词分析的不足,提出了一个兼顾中低频关键词的选词方案。方案中提出删除通用高频关键词的设想,解决通用高频关键词的复分难题;把共现关系较强的中低频关键词纳入共词分析之中,提高关键词的代表性。通过多维尺度图和聚类树状图的对比分析,发现这种共词分析方法相对传统的高频关键词共词分析关键词聚合度更高,组团间关系更明晰,更能揭示研究领域的主题结构,是一种改进共词分析效果的有效方法。

By studying the highly cited papers by years in library and information science field, the paper points out the shortcomings of high frequency keyword co-word analysis, arid proposes a word selection program that acknowledges medium and low frequency keywords. It recommends deleting the high-frequency keywords and including medium and low frequency keywords that boast strong co- occurrence relationship into analysis, as well as improving representativeness of keywords. Through the comparison and analysis of multidimensional scale graph and clustering tree diagram, the paper verifies that the new method is better than the traditional high-frequency keyword co-word analysis, with higher degree of aggregation, clearer relationship between groups, and increased efficiency to reveal the thematic structure of the research field.