When standard network measures fail to rank journals: A theoretical and empirical analysis.

Quant. Sci. Stud.(2022)

引用 0|浏览4
暂无评分
摘要
Journal rankings are widely used and are often based on citation data in combination with a network perspective. We argue that some of these network-based rankings can produce misleading results. From a theoretical point of view, we show that the standard network modelling approach of citation data at the journal level (i.e., the projection of paper citations onto journals) introduces fictitious relations among journals. To overcome this problem, we propose a citation path perspective, and empirically show that rankings based on the network and the citation path perspective are very different. Based on our theoretical and empirical analysis, we highlight the limitations of standard network metrics, and propose a method to overcome these limitations and compute journal rankings.
更多
查看译文
关键词
citation network, citation paths, journal rankings, ranking bias, PageRank
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要