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Issue No. 04 - July/August (2010 vol. 25)
ISSN: 1541-1672
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.
social media, social computing, social learning, machine learning, data mining, Web 2.0, intelligent systems

W. Mao, Z. Zhou, Q. Yang, W. Li and N. N. Liu, "Social Learning," in IEEE Intelligent Systems, vol. 25, no. , pp. 9-11, 2010.
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