摘要
[目的/意义]学术成果评价是推进哲学社会科学健康发展的重要因素,长期以来,传统同行评议和科学计量学方法在哲学社会科学学术成果评价中暴露出的问题越来越多,挑战固有方法的统治地位、开发有针对性的评价策略已刻不容缓。文章试图探索大数据环境下哲社学术成果评价的变革及其实现,特别是提出了大数据思维下的哲社学术成果的评价指标体系。[方法/过程]基于比较分析和综合分析,对传统哲学社会科学评价方法的弊端进行分析,然后对大数据给哲学社会科学评价带来的改变进行分析,最后提出基于大数据环境的哲学社会科学评价策略和指标体系。[结果/结论]提出大数据时代哲学社会科学学术成果评价的策略:由引文著录分析转向多维度的引用内容与行为分析,由面向成果的阶段性静态评价转向以“学术活动”为中心的全过程动态评价,由学术影响力评价转向学术价值和社会效益评价。在此基础上,构建由两个一级指标、5个二级指标和34个三级指标组成的大数据背景下哲学社会科学学术成果评价指标体系。
[Purpose/significance] To solve some defects of peer review and scientometrics methods in the evaluation of philosophy and social sciences academic outputs, the reform and realization of the evaluation of the academic achieve-ments are explored, especially the evaluation index system of the academic achievements of philosophy and social sciences based on the big data thinking are designed. [Method/process] Based on the comparative analysis and comprehensive a- nalysis, this paper analyzes the disadvantages of the traditional philosophy and social sciences evaluation methods, and then analyzes the changes brought by the big data to the philosophy and social sciences evaluation, finally, it puts forward the philosophy and social sciences evaluation strategies and the index systems based on the big data environment. [ Re- suit/conclusion] In big data era, it is possible to analyze the semantics and its relevance based on all-round academic contents and activity data. By using the citation content and behavior evaluation, the academic activities-centered whole process dynamic evaluation, academic value and social function evaluation, value of academic achievements of philosophy and social sciences can be truly, comprehensively and objectively reflected. Based on above research, an index system for evaluation of academic achievements of philosophy and social sciences is constructed, which is composed of two first -level indicators, five two-level indicators and 34 three-level indicators.
作者
李品
杨建林
Li Pin;Yang(Jianlin School of Information Management,Nanjing University,Nanjing 210023;Jiangsu Key Laboratory of Data Engineering & Knowledge Service,Nanjing University,Nanjing 210023)
出处
《图书情报工作》
CSSCI
北大核心
2018年第16期5-14,共10页
Library and Information Service
基金
江苏省社会科学基金重大项目“习近平总书记构建中国特色哲学社会科学重大命题研究”(项目编号:16ZD004)研究成果之一
关键词
哲学社会科学
学术成果
成果评价
大数据
philosophy and social
sciences
academic output output
evaluation
big data