Social computing concerns the study of social behavior and context based on computational systems. Behavioral modeling reproduces the social behavior, and allows for experimenting, scenario planning, and deep understanding of behavior, patterns, and potential outcomes. The pervasive use of computer and Internet technologies creates an unprecedented environment where people can share opinions and experiences, exchange ideas, offer suggestions and advice, debate and even conduct experiments. Social computing facilitates behavioral modeling in model building, analysis, pattern mining, anticipation, and prediction.

This volume presents material from the second interdisciplinary workshop focused on employing social computing for behavioral modeling and prediction. The book provides a platform for disseminating results and developing new concepts and methodologies aimed at advancing and deepening our understanding of social and behavioral computing to aid critical decision making. The contributions from this year's conference, incorporating views from government, industry and academia, address themes such as:

• social network analysis
• modeling
• machine learning and data mining
• social behaviors and social order
• public health
• cultural aspects
• trust, privacy, and intention
• opinion, preference, influence, and diffusion
• extreme events
• assessment and validation
• effects and search

Researchers, practitioners and graduate students from sociology, behavioral and computer science, psychology, cultural study, information systems, political science, and operations research are certain to find this a fascinating and essential resource.