Social Computing with Artificial Intelligence

1. Front Matter

   Pages i-xii

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2. Introduction

   • Xun Liang

   Pages 1-7

3. Data

   1. Front Matter

      Pages 9-9

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   2. Data Collection

      • Xun Liang

      Pages 11-19

   3. Data Processing Methodology

      • Xun Liang

      Pages 21-23

4. AI Models and Algorithms

   1. Front Matter

      Pages 25-25

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   2. Supervised and Unsupervised Learning Models

      • Xun Liang

      Pages 27-82

   3. State-of-the-Art Artificial Intelligence Algorithms

      • Xun Liang

      Pages 83-125

   4. Social Network Data Mining and Knowledge Discovery

      • Xun Liang

      Pages 127-153

   5. Social Networks Structure Analysis and Online Community Discovery

      • Xun Liang

      Pages 155-178

   6. Social Network Propagation Mechanism and Online User Behavior Analysis

      • Xun Liang

      Pages 179-230

5. Applications

   1. Front Matter

      Pages 231-231

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   2. Social Computing Application in Public Security and Emergency Management

      • Xun Liang

      Pages 233-242

   3. Social Computing Application in Business Decision Support

      • Xun Liang

      Pages 243-248

   4. Social Computing Application in Unsupervised Oracle Handwriting Recognition Based on Pic2Vec Image Content Mapping

      • Xun Liang

      Pages 249-255

   5. Social Computing Application in Online Crowd Behavior and Psychology

      • Xun Liang

      Pages 257-276

6. Back Matter

   Pages 277-289

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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.

• Social Computing
• Online Social Networks
• Social Networks Structure Analysis
• Online Community Discovery
• Online Users Information Analysis
• Network Propagation Mechanism
• Social Computing Application
• Online Crowd Behavior
• Deep Learning in Social Computing
• Machine Learning in Social Computing

• School of Information, Renmin University of China, Beijing, China

  Xun Liang

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. 

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