...
首页> 外文期刊>Journal of informetrics >Understanding and modeling diverse scientific careers of researchers
【24h】

Understanding and modeling diverse scientific careers of researchers

机译:了解和建模研究人员的各种科学职业

获取原文
获取原文并翻译 | 示例
           

摘要

This paper analyzes the diverse scientific careers of researchers in order to understand the key factors that could lead to a successful career. Essentially, we intend to answer some specific questions pertaining to a researcher's scientific career - What are the local and the global dynamics regulating a researcher's decision to select a new field of research at different points of her entire career? What are the suitable quantitative indicators to measure the diversity of a researcher's scientific career? We propose two entropy-based metrics to measure a researcher's choice of research topics. Experiments with large computer science bibliographic dataset reveal that there is a strong correlation between the diversity of the career of a researcher and her success in scientific research in terms of the number of citations. We observe that while most of the researchers are biased toward either adopting diverse research fields or concentrating on very few fields, a majority of the prominent researchers tend to follow a typical "scatter-gather" policy - although their entire careers are immensely diverse with different types of fields selected at different time periods, they remain focused primarily in at most one or two fields at any particular time point of their career. Finally, we propose a stochastic model which, quite accurately, mimics the notion of field selection process observed in the real publication dataset. (C) 2014 Elsevier Ltd. All rights reserved.
机译:本文分析了研究人员的各种科学职业,以了解可能导致职业成功的关键因素。从本质上讲,我们打算回答一些与研究人员的科学职业有关的特定问题-限制研究人员在其整个职业生涯中选择新的研究领域的决定的本地和全球动力是什么?什么是合适的量化指标来衡量研究人员科学生涯的多样性?我们提出了两个基于熵的指标来衡量研究者对研究主题的选择。大型计算机科学书目数据集的实验表明,就引用次数而言,研究人员的职业多样性与她在科学研究中的成功之间有着很强的相关性。我们观察到,尽管大多数研究人员偏向于采用不同的研究领域或只专注于极少数领域,但大多数杰出的研究人员倾向于遵循典型的“分散聚集”政策-尽管他们的整个职业生涯因不同而千差万别在不同时期选择的领域类型,他们在职业的任何特定时间点仍主要集中在最多一两个领域。最后,我们提出了一种随机模型,该模型非常准确地模仿了在实际出版物数据集中观察到的字段选择过程的概念。 (C)2014 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号