Features

• Introduces key concepts, new challenges, and underlying principles of social computing and data mining
• Covers key topics, such as social network analysis, social media, text analysis, and web mining
• Reviews classic concepts and algorithms in graph theory, game theory, computer science, and statistics
• Includes real-world examples and case studies of recent Web 2.0 developments
• Provides a convenient portal for researching and teaching social computing and data mining

Summary

This book begins with a brief introduction to social computing and a review of classic graph theory and game theory. It then examines the data used to construct social networks, focusing on emerging Web 2.0 technologies and social networking websites, such as Facebook and MySpace. The book also explores data mining for social network extraction and analysis, presenting link and graph mining algorithms, such as subgraph discovery and clustering. In the last section, the authors provide case studies to illustrate concepts and principles as well as to demonstrate how to integrate components in order to solve real-world problems.