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Guest editorial: Special issue on data mining technologies for computational social science

机译:客座社论:关于计算社会科学的数据挖掘技术的特刊

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摘要

The article focuses on data mining technologies for computational social science. The emergence of online social network sites and web 2.0 applications generate a large volume of valuable data. This greatly stimulates the development of computational social science, which tries to solve the research problems in traditional social science with the help of computational technologies. In addition to novel computational models, it would also be interesting to see the application of data mining techniques in real social problems. With the burst of various online social network, people are also interested in mining the people emotions from those online data. There are many fundamental problems in social sciences, such as detecting underlying communities, analyzing the mechanism of a specific behavior (social activity) and discovering the evolutionary patterns in a community.
机译:本文重点介绍用于计算社会科学的数据挖掘技术。在线社交网站和Web 2.0应用程序的出现产生了大量有价值的数据。这极大地刺激了计算社会科学的发展,它试图借助计算技术来解决传统社会科学中的研究问题。除了新颖的计算模型外,看到数据挖掘技术在实际社会问题中的应用也将很有趣。随着各种在线社交网络的爆发,人们也有兴趣从这些在线数据中挖掘人们的情感。社会科学中存在许多基本问题,例如检测基础社区,分析特定行为(社会活动)的机制以及发现社区的进化模式。

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