PageRank-based prediction of award-winning researchers and the impact of citations

作者：

Highlights：

• Almost two million textual metadata records on computer science papers from Web of Science were retrieved.

• 25 cumulative subsets covering the period 1990–2014 of a large citation network of authors were analyzed.

• Past and future Codd Award and Turing Award winners were used to evaluate PageRank-based and citations-based rankings.

• PageRank-based methods outperform citations-based techniques if the relative ranks of awardees are considered.

摘要

•Almost two million textual metadata records on computer science papers from Web of Science were retrieved.•25 cumulative subsets covering the period 1990–2014 of a large citation network of authors were analyzed.•Past and future Codd Award and Turing Award winners were used to evaluate PageRank-based and citations-based rankings.•PageRank-based methods outperform citations-based techniques if the relative ranks of awardees are considered.

论文关键词：PageRank,Scholars,Citations,Rankings,Web of science,Awards

论文评审过程：Received 6 February 2017, Revised 22 September 2017, Accepted 25 September 2017, Available online 12 October 2017, Version of Record 12 October 2017.

论文官网地址：https://doi.org/10.1016/j.joi.2017.09.008