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杂谈

Googlers across the company actively engage with the scientific community by publishing technical papers, contributing open-source packages, working on standards, introducing new APIs and tools, giving talks and presentations, participating in ongoing technical debates, and much more. Our publications offer technical and algorithmic advances, feature aspects we learn as we develop novel products and services, and shed light on some of the technica
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杂谈

David Liben-Nowell, and Jon Kleinberg

*Department of Computer Science, Carleton College, Northfield, MN 55057; and {ddagger}Department of Computer Science, Cornell University, Ithaca, NY 14853

Edited by Ronald L. Graham, University of California at San Diego, La Jolla, CA, and approved January 25, 2008 (received for review September 6, 2007)



Although information, news, and opinions continuously circulate in the worldwide social network, the actual mechanics of how any single piece of information spreads on a global scale have been a mystery. Here, we trace such information-spreading processes at a person-by-person level using methods to reconstruct the propagation of massively circulated Internet chain letters. We find that rather than fanning out widely, reaching many people in very few steps according to 'small-world' princip
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(2008-01-29 18:14)
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杂谈

 http://abeautifulwww.com/

一个网站,应该类似于Slashdot的这种群体博客,里面有很多关于WWW数据的可视化,比较有意思。例如:

Another Visualization of the Netflix Prize Dataset 讲的是Netflix的可视化,图片很漂亮。
http://abeautifulwww.com/2007/04/03/another-visualization-of-the-netflix-prize-dataset/

Visualizing the ‘Power Struggle’ in Wikipedia 是关于wikipedia的。
http://abeautifulwww.com/2007/05/20/visualizing-the-power-struggle-in-wikipedia/

忘了圈里有没有这个信息了。贴出来共享一下。:)
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http://www.santafe.edu/~aaronc/powerlaws/

作者是 Aaron Clauset, Cosma R. Shalizi and M.E.J. Newman。
还没来得及看。应该不错啊。
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这本书的作者保罗·希利亚斯(Paul Cilliers)曾获得电气工程学位和哲学博士学位,专长于利用网络进行模式识别等,后辗转进入某大学哲学系,教授哲学课程。一个有着工科背景的哲学教授,对于现实世界的观照自然是更加贴进现实一些。

      

在这本书里,所谓的“后现代主义”,他们的观点是:不应该以单个或者根本性原则来分析复杂现象,而应该承认不可能对真正复杂的事物给出单一的、排他的叙述。不过承认复杂性,并不意味着“怎样都行”的结论。也许在后现代主义者眼中的世界并不如爱因斯坦眼中的世界那样由一个统一的终极方程来约束着。

      

 

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PNAS的Online Print上有Rosvall and Bergstrom的一篇论文,
An information-theoretic framework for resolving community structure in complex networks

该文提出了一种新的社团发现的算法。他们把复杂网络中的社团结构发现问题看作是如何最有效压缩这个网络的问题。如下图所示,即如何寻找一个对社团之间连通方式的描述Y来简化对整个复杂网络X的描述。该方法采用最大化X和Y之间互信息来寻找最优压缩方案。实验表明,该算法相对于Girvan-Newman算法来讲,对于社团之间节点不均匀或链接数不均匀的情况,具有较好的效果。同时,该算法可以通过最小化从Y解压回X所需信息的最小描述长度(minimum description length)来寻找社团的数量。在社团之间的节点不均匀或链接数不均匀的情况下,Girvan-Newman往往高估社团数量,而该算法则有较好效果。作者通过模拟退火方法实现该算法,能够处理最多10000个节点的网络。但文中指出实际上可以采取贪婪算法等实现该算法,以期解决更大规模网络的社团发现问题。

http://s11.sinaimg.cn/orignal/574a437f8115e167f623a
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http://www.cscs.umich.edu/~crshalizi/notebooks/community-discovery.html

Community Discovery Methods for Complex Networks

28 Mar 2007 18:55

Given: a network, especially a large one, directed or not, weighted or not. Desired: a sensible decomposition of the graph into sub-graphs, where in some reasonable sense the nodes in each sub-graph have more to do with each other than with outsiders, i.e., form communities. This is also called 'module detection'.

This seems like a really useful idea to apply to problems I'm interested in, in neural synchronization; also a place where there could stand to be more interchange between statistics and

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