Liu / Salerno / Young Social Computing, Behavioral Modeling, and Prediction

1. Auflage 2008
ISBN: 978-0-387-77672-9
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 264 Seiten, eBook

Social computing concerns the study of social behavior and context based on computational systems. Behavioral modeling reproduces the social behavior, and allows for experimenting with and deep understanding of behavior, patterns, and potential outcomes. The pervasive use of computer and Internet technologies provides an unprecedented environment where people can share opinions and experiences, offer suggestions and advice, debate, and even conduct experiments. Social computing facilitates behavioral modeling in model building, analysis, pattern mining, anticipation, and prediction. The proceedings from this interdisciplinary workshop provide a platform for researchers, practitioners, and graduate students from sociology, behavioral and computer science, psychology, cultural study, information systems, and operations research to share results and develop new concepts and methodologies aimed at advancing and deepening our understanding of social and behavioral computing to aid critical decision making.

Zielgruppe

Research

Autoren/Hrsg.

Liu, Huan

Salerno, John

Young, Michael J.

Inhaltsverzeichnis

Rational Choice Theory: A Forum for Exchange of Ideas between the Hard and Social Sciences in Predictive Behavioral Modeling.- The SOMA Terror Organization Portal (STOP): social network and analytic tools for the real-time analysis of terror groups.- The Sociology of Alien Rule.- The DoD Encounters the Blogosphere.- Integrating Multi-Agent Technology with Cognitive Modeling to Develop an Insurgency Information Framework (IIF).- Stochastic Opponent Modeling Agents: A Case Study with Hezbollah.- An approach to modeling group behaviors and beliefs in conflict situations.- Computational Models of Multi-National Organizations.- Clustering of Trajectory Data obtained from Soccer Game Records – A First Step to Behavioral Modeling –.- Mobile Phone Data for Inferring Social Network Structure.- Human Behavioral Modeling Using Fuzzy and Dempster–Shafer Theory.- Online Behavioral Analysis and Modeling Methodology (OBAMM).- Mining for Social Processes in Intelligence Data Streams.- An Ant Colony Optimization Approach to Expert Identification in Social Networks.- Attribution-based Anomaly Detection: Trustworthiness in an Online Community.- Particle Swarm Social Model for Group Social Learning in Adaptive Environment.- Social Network Analysis: Tasks and Tools.- Behavioral Entropy of a Cellular Phone User.- Community Detection in a Large Real-World Social Network.- Where are the slums? New approaches to urban regeneration.- A Composable Discrete-Time Cellular Automaton Formalism.- Designing Group Annotations and Process Visualizations for Role-Based Collaboration.- Modeling Malaysian Public Opinion by Mining the Malaysian Blogosphere.- Reading Between the Lines: Human-centred Classification of Communication Patterns and Intentions.- Metagame Strategies of Nation-States, withApplication to Cross-Strait Relations.- Automating Frame Analysis.- Using Topic Analysis to Compute Identity Group Attributes.