Predicting future influence of papers, researchers, and venues in a dynamic academic network
作者：
Highlights：
• Dynamic academic networks are introduced for predicting future influence of entities.
• Every researcher or venue per year is treated as a separate entity.
• Seven types of relations among papers, authors, and venues are extracted and used for prediction.
• Both publication age and recent citations are considered for a balanced treatment of old and new papers.
摘要
•Dynamic academic networks are introduced for predicting future influence of entities.•Every researcher or venue per year is treated as a separate entity.•Seven types of relations among papers, authors, and venues are extracted and used for prediction.•Both publication age and recent citations are considered for a balanced treatment of old and new papers.
论文关键词：Academic influence prediction,Dynamic academic network,Paper citation,Mutual reinforcement
论文评审过程：Received 27 May 2019, Revised 9 March 2020, Accepted 10 March 2020, Available online 6 May 2020, Version of Record 6 May 2020.
论文官网地址：https://doi.org/10.1016/j.joi.2020.101035
