美赛c题翻译.docx

Using Networks to Measure Influence and Impact（使用网络系统测定影响因子（因素）（使用网络系统测定影响因子（因素） ））One of the techniques to determine influence of academic research is to build and measure properties of citation or co-author networks. 衡量学术研究的方 法之一是建立和衡量检索频率或共同作者Co-authoring a manuscript usually connotes a strong influential connection between researchers. 合著论文通常 表明研究者之间有很强的联系One of the most famous academic co-authors was the 20th-century mathematician Paul Erdös who had over 500 co-authors and published over 1400 technical research papers. 合著论文最有名的例子是 20世纪的数学家Paul Erdös ，他有500多个合著论文者，且发表了1400篇研究 论文。

It is ironic, or perhaps not, that Erdös is also one of the influencers in building the foundation for the emerging interdisciplinary science of networks, particularly, through his publication with Alfred Rényi of the paper “On Random Graphs” in 1959. 或许有些沨刺意味，或许没有，Erdös 还是建立刚 刚出现的跨学科网络的最有影响力的人之一特别是通过与Alfred Rényi 合著 论文《随机图像》在1959年的发表Erdös’s role as a collaborator was so significant in the field of mathematics that mathematicians often measure their closeness to Erdös through analysis of Erdös’s amazingly large and robust co-author network (see the website http://www.oakland.edu/enp/ ). Erdös 作 为合著者在数学领域的功老如此之大以至于数学家们经常通过分析Erdös 的强 大的合著网络来测定自己与Erdös 的差距。

The unusual and fascinating story of Paul Erdös as a gifted mathematician, talented problem solver, and master collaborator is provided in many books and on-line websites (e.g., http://www- history.mcs.st-and.ac.uk/Biographies/Erdos.html). Perhaps Paul Erdös作为天 才的数学家，天才的问题解者，精通的合著者的传奇故事经常见诸众多书籍和 网站 his itinerant lifestyle, frequently staying with or residing with his collaborators, and giving much of his money to students as prizes for solving problems, enabled his co-authorships to flourish and helped build his astounding network of influence in several areas of mathematics. 或许他的独 特的生活方式，他经常和合作者呆在或住在一起，她给解决问题的学生大量奖 金等这些方式使他的合作者不断进取，而且帮助他在数学的诸多领域建立了影 响网络。

In order to measure such influence as Erdös produced, there are network-based evaluation tools that use co-author and citation data to determine impact factor of researchers, publications, and journals. 为了衡量 诸如Erdös 等产生的影响，这有一些基于网络的评估工具，其使用合著者和索 引数据来测定研究者，期刊和杂志的影响因素Some of these are Science Citation Index, Hfactor, Impact factor, Eigenfactor, etc. 这其中包括，Science Citation Index, Hfactor, Impact factor, Eigenfactor, 等索引指标Google Scholar is also a good data tool to use for network influence or impact data collection and analysis. Google Scholar 同样是一个很好的数据工具用以测定 网络影响，影像重要数据的收集和分析。

Your team’s goal for ICM2014 is to analyze influence and impact in research networks and other areas of society. Your tasks to do this include: ICM2014比赛中，你们队的任务是分析研究领域和社会其他领域的影响因素你们的任务包括： 1) Build the co-author network of the Erdos1 authors (you can use the fi le from the website https://files.oakland.edu/users/grossman/enp/Erdos1.ht ml or the one we include at Erdos1.htm ). 建立 Erdos1 的合作者的合著网 络（可以使用如下网址的文章，https://files.oakland.edu/users/grossman/enp/ Erdos1.html or the one we include at Erdos1.htm ) You should build a co-author network of the approximately 510 researchers from the file Erd os1, who coauthored a paper with Erdös, but do not include Erdös. 你应 从文件 Erdos1 中建立大约有 510 名研究者的合著网络，这些合著者与 Erdös 合著论文，但不包括 Erdös 本人。

This will take some skilled data extractio n and modeling efforts to obtain the correct set of nodes (the Erdös coa uthors) and their links (connections with one another as coauthors). 这需 要熟练的数据挖掘和模型建立来获取正确的节点（Erdös 合著者）和他们的联 系（合著者们之间的联系）There are over 18,000 lines of raw data in Erd os1 file, but many of them will not be used since they are links to peopl e outside the Erdos1 network. 在文件 Erdos1 中，有超过 18000 条原始数据 ，但很多将不被使用，因为它们与 Erdos1 网络系统之外的人相联系If neces sary, you can limit the size of your network to analyze in order to calibr ate your influence measurement algorithm. 如有需要，为了校准你的影响测 量算法，你可以限定你的网络规模来进行分析。

Once built, analyze the properties of this network. (Again, do not include Erdös --- he is the most influential and would be connected to all nodes in the network. In this case, it’s co-authorship with him that builds the network, but he is not part of the network or the analysis.) 一旦建成，分析这个网络的特性 （同样，不包括埃尔德什---他是最有影响力的，并会连接到网络中的所有节点在这 种情况下，它是与合作者共同建立了网络，但他不是网络部分也不是分析的对象）2) Develop influence measure(s) to determine who in this Erdos1 network has significant influence within the network. Consider who has published important works or connects important researchers within Erdos1. Again, assume Erdös is not there to play these roles. 找出影响的措施（S），以确定谁在这个 Erdos1 网 络中有显著影响。

考虑谁曾发表重要论文或在 Erdos1 网络中连接重量级的研究人员 同样，假设Erdös（埃尔德什）不是那里扮演这些角色3) Another type of influence measure might be to compare the significance of a research paper by analyzing the important works that follow from its publication. Choose some set of foundational papers in the emerging field of network science either from the attached list (NetSciFoundation.pdf) or papers you discover. Use these papers to analyze and develop a mo。