计算网络科学:从数据到社会模型

Przemyslaw Kazienko
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引用次数: 0

摘要

通过数据驱动的方法,计算机科学改变了所有其他科学。它也指网络科学和更具体的领域:社会网络分析。社会网络可以从四个主要的角度来研究:计算机科学处理的数据、物理学发展的模型、认知科学和神经科学分析的人类感知以及社会学提供的调查研究。这四种方法相辅相成,使社交网络成为最跨学科的领域之一。我们对时间社会网络的新研究结合了自动追踪的人类活动和他们从定期访谈中获得的感知,将作为这种同居的一个例子。此外,还将讨论复杂网络中信息扩散的最新研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computational network science: From data to social models
Through its data-driven approach computer science change all other sciences. It also refers network science and more specific domain: social network analysis. Social networks can be studied from four main perspectives: data processed by computer science, models developed by physics, human perception analyzed by cognitive science and neuroscience as well as survey research provided by sociology. All four complement each other making social networks one of the most interdisciplinary field. Our new studies on temporal social networks combining automatically traced human activities with their perception derived from periodical interviews will be presented as an example for such cohabitation. Additionally, recent research on information diffusion in complex networks will be discussed.
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