Chapter 1. Introduction.- Chapter 2. Data Collection.- Chapter 3. Data Processing Methodology.- Chapter 4. Supervised and Unsupervised Learning Models.- Chapter 5. State-of-the-Art Artificial Intelligence Algorithms.- Chapter 6. Social Network Data Mining and Knowledge Discovery.- Chapter 7. Social Network Structure Analysis and Online Community Discovery.- Chapter 8. Social Network Propagation Mechanism and Online User Behavior Analysis.- Chapter 9. Social Computing Application in Public Security and Emergency Management.- Chapter 10. Social Computing Application in Business Decision Support.- Chapter 11. Social Computing Application in Unsupervised Oracle Handwriting Recognition Based on Pic2Vec Image Content Mapping.- Chapter 12. Social Computing Application in Online Crowd Behavior and Psychology.
Xun Liang is a Professor at Renmin University of China. He is the chief expert of a major National Social Science Foundation project, and the leader of a key National Natural Science Foundation of China project. He has been engaged in research on network information mining, social computing and machine learning for many years, and has published more than 200 papers and 14 specialized books, and has applied for more than 10 national invention patents, one international patent and one American patent. He also serves as chairman of the procedural committees of national and international conferences and as a special invited theme presenter.
This book provides a comprehensive introduction to the application of artificial intelligence in social computing, from fundamental data processing to advanced social network computing. To broaden readers’ understanding of the topics addressed, it includes extensive data and a large number of charts and references, covering theories, techniques and applications. It particularly focuses on data collection, data mining, artificial intelligence algorithms in social computing, and several key applications of social computing application, and also discusses network propagation mechanisms and dynamic analysis, which provide useful insights into how information is disseminated in online social networks. This book is intended for readers with a basic knowledge of advanced mathematics and computer science.