Author ranking evaluation at scale

作者：

Highlights：

• We make a large test data set available comprising well-established researchers.

• PageRank performs better than citation counts in identifying these researchers.

• Paper impact scores should be evenly divided among co-authors.

• Removing self-citations improves all metrics for well-established researchers.

摘要

•We make a large test data set available comprising well-established researchers.•PageRank performs better than citation counts in identifying these researchers.•Paper impact scores should be evenly divided among co-authors.•Removing self-citations improves all metrics for well-established researchers.

论文关键词：Author indicators,Author ranking,Citation analysis,PageRank

论文评审过程：Received 9 October 2017, Revised 1 June 2018, Accepted 10 June 2018, Available online 27 June 2018, Version of Record 27 June 2018.

论文官网地址：https://doi.org/10.1016/j.joi.2018.06.004