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- | ====== Quantitative Analysis on Science of Science: Impact, Credit, Talent and Gender ====== | + | ====== 科学学的定量分析:影响力、信誉、天才和性别 ====== |
+ | *时间:2018年05月25日 14:00-15:30 | ||
+ | *地点:北京工业大学经管楼B301 | ||
+ | |||
+ | ===== 报告人简介 ===== | ||
+ | **黄俊铭**博士,2007年本科毕业于清华大学物理系,2014年在中科院计算所获得博士学位,导师是李国杰院士。黄俊铭博士2015年赴美国东北大学复杂网络中心艾伯特—拉斯洛 ·巴拉巴西(Albert-László Barabási)课题组做博士后至今。黄博士的研究兴趣是科学学和社会网络分析。Albert-László Barabási是全球复杂网络研究的权威,无标度网络的创立者。 | ||
+ | |||
+ | ===== 报告大纲 ===== | ||
+ | **Quantitative Analysis on Science of Science: Impact, Credit, Talent and Gender** | ||
+ | |||
+ | Understanding the fundamental mechanism of scientific discoveries is instrumental for policy design that aims at accelerating the scientific progress. The recent availability of large-scale digitized data on scientific publication, impact and collaboration provides opportunities to quantitatively explore hidden patterns governing the intrinsic of science. With a combination of tools from statistics and network science, we explore several questions that lead to quantitative understanding of scientific practice: How do scholar outputs gain impact from the scientific community? How are credits allocated among collaborators? How predictable a scientist would see his/her representative work in career? How do gender differences emerge and evolve in the history of science? With a deeper understanding of those factors behind scientific practice, we provide insights to capture the unfolding of science and suggestions to design policy and interventions | ||