A network-based and multi-parameter model for finding influential authors
作者：
Highlights：
• Katz–Bonacich centrality is adopted to define the network prestige.
• Author's influence is measured by the change of network prestige.
• The model's time complexity is low.
• The implications of two parameters are uncovered by simulation analysis.
• A comprehensive application is designed to validate the model's functions.
摘要
•Katz–Bonacich centrality is adopted to define the network prestige.•Author's influence is measured by the change of network prestige.•The model's time complexity is low.•The implications of two parameters are uncovered by simulation analysis.•A comprehensive application is designed to validate the model's functions.
论文关键词：Author's influence,Network analysis,Coauthor network,Multi-parameter model,Simulation,Evaluation techniques for scientific output
论文评审过程：Received 3 June 2014, Revised 18 July 2014, Accepted 22 July 2014, Available online 12 August 2014.
论文官网地址：https://doi.org/10.1016/j.joi.2014.07.007
