Reading Group

Wang Cheng-Jun edited this page Dec 25, 2016 · 4 revisions

计算传播学是计算社会科学的重要分支。它主要关注人类传播行为的可计算性基础,以传播网络分析、传播文本挖掘、数据科学等为主要分析工具,(以非介入地方式)大规模地收集并分析人类传播行为数据,挖掘人类传播行为背后的模式和法则,分析模式背后的生成机制与基本原理,可以被广泛地应用于数据新闻和计算广告等场景,注重编程训练、数学建模、可计算思维。

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  1. From old wars to new wars and global terrorism Johnson, N., Spagat, M., Restrepo, J., Bohorquez, J., Suarez, N., & Restrepo, E., et al. (2005). Nature
  2. Common ecology quantifies human insurgency Juan Camilo Bohorquez1, Sean Gourley, Alexander R. Dixon, Michael Spagat & Neil F. Johnson. 2009 Nature
  3. Fundamental structures of dynamic social networks. Vedran Sekara, Arkadiusz Stopczynskia, and Sune Lehmann, 2016. PNAS doi:10.1073/pnas.1602803113
  4. A network framework of cultural history. Maximilian Schich,* Chaoming Song, Yong-Yeol Ahn, Alexander Mirsky, Mauro Martino, Albert-László Barabási, Dirk Helbing. 2014. 345: 6196 Science
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  7. Predictability of population displacement after the 2010 Haiti earthquake Xin Lua,b,1,2, Linus Bengtssona,1,2, and Petter Holmea,b, PNAS 2012
  8. Xudong Cao (2014) A practical theory for designing very deep convolutional neural networks. Unpublished.
  9. Guimera, Roger, Brian Uzzi, Jarrett Spiro, and Luis A. Nunes Amaral. Team Assembly Mechanisms Determine Collaboration Network Structure and Team Performance, Science, 2005, 308:697-702.
  10. Jean, N., Burke, M., Xie, M., Davis, W. M., Lobell, D. B., & Ermon, S. (2016). Combining satellite imagery and machine learning to predict poverty. Science, 353(6301), 790-794.
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