Should citations be field-normalized in evaluative bibliometrics? An empirical analysis based on propensity score matching
作者：
Highlights：
• We investigated the question how strong fields influence citation counts of papers.
• Can field differences be traced back to factors possibly influencing citations (FICs)?
• We considered 13 variables as FICs, e.g., number of pages, co-authors, and cited references.
• We applied propensity score matching as statistical method to make causal statements.
• The results revealed that field differences did not completely vanish but were dramatically reduced.
摘要
•We investigated the question how strong fields influence citation counts of papers.•Can field differences be traced back to factors possibly influencing citations (FICs)?•We considered 13 variables as FICs, e.g., number of pages, co-authors, and cited references.•We applied propensity score matching as statistical method to make causal statements.•The results revealed that field differences did not completely vanish but were dramatically reduced.
论文关键词：Scientometrics,Bibliometrics,Field-normalization,Propensity score matching,Citation impact
论文评审过程：Received 10 June 2020, Revised 18 September 2020, Accepted 21 September 2020, Available online 7 November 2020, Version of Record 7 November 2020.
论文官网地址：https://doi.org/10.1016/j.joi.2020.101098
