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Social Learning
July/August 2010 (vol. 25 no. 4)
pp. 9-11
Qiang Yang, Hong Kong University of Science and Technology
Zhi-Hua Zhou, Nanjing University
Wenji Mao, Chinese Academy of Sciences
Wei Li, Beihang University
Nathan Nan Liu, Hong Kong University of Science and Technology
In recent years, social behavioral data have been exponentially expanding due to the tremendous success of various outlets on the social Web (aka Web 2.0) such as Facebook, Digg, Twitter, Wikipedia, and Delicious. As a result, there's a need for social learning to support the discovery, analysis, and modeling of human social behavioral data. The goal is to discover social intelligence, which encompasses a spectrum of knowledge that characterizes human interaction, communication, and collaborations. The social Web has thus become a fertile ground for machine learning and data mining research. This special issue gathers the state-of-the-art research in social learning and is devoted to exhibiting some of the best representative works in this area.

1. F.-Y. Wang et al., "Social Computing: From Social Informatics to Social Intelligence," IEEE Intelligent Systems, vol. 22, no. 2, 2007, pp. 79–83.
2. D. Zeng, F.-Y. Wang, and K.M. Carley, "Guest Editors' Introduction: Social Computing," IEEE Intelligent Systems, vol. 22, no. 5, 2007, pp. 20–22.

Index Terms:
social media, social computing, social learning, machine learning, data mining, Web 2.0, intelligent systems
Citation:
Qiang Yang, Zhi-Hua Zhou, Wenji Mao, Wei Li, Nathan Nan Liu, "Social Learning," IEEE Intelligent Systems, vol. 25, no. 4, pp. 9-11, July-Aug. 2010, doi:10.1109/MIS.2010.103
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