基于ESI的潜力学科预测模型修正和实证分析

A Modified Model for Potential Disciplines Forecast and Empirical Analysis Based on ESI

【目的/意义】ESI数据库和InCites数据库更新时间的差异和数据源的差异导致潜力学科预测不准确。本文针对22个学科在ESI数据库和InCites数据库的数据偏差进行统计分析,计算出22个学科误差修正因子,并建立ESI的潜力学科修正模型,以便消除学术机构在预测潜力学科过程中出现的偏差。【方法/过程】本文采用文献计量学、层次分析等多种方法进行研究。【结果/结论】研究结果表明,当误差修正因子<0.9时,数据偏差较大,经过修正之后的ESI潜力学科预测模型更为准确,对学术机构制定学科发展战略、合理配置资源具备参考价值。

【Purpose/significance】The differences in the update time and the differences in the data sources about ESI database and InCites database lead to inaccurate prediction of the potential discipline. For 22 subjects in ESI database and InCites database data deviation statistical analysis, to calculate the error correction factor and establish a modified model to forecast ESI potential disciplines, in order to eliminate the deviation of academic institutions in the prediction process.【Method/process】In this paper, we use the literature metrology, analytic hierarchy process and other methods .【Result/conclusion 】The research results show that when the error correction factor < 0.9, the data deviation is bigger, the modified ESI potential prediction model is more accurate, it has reference value to the rational allocation of resources and the drafting of discipline development strategy for academic institutions.