Social science research is fragmented by the widely differing and seemingly contradictory approaches used by the different disciplines of the social sciences to explain human action. Attempts at integrating different social science approaches to explain action have often been frustrated by the difficulty of incorporating cultural assumptions into rational choice theories without robbing them of their generality or making them too vague for predictions. Another problem has been the major disagreements among cultural theorists regarding the ways in which culture affects preferences and beliefs. This book provides a general model of preference and belief formation, addressing the largest unresolved issue in rational choice theories of action. It attempts to play a bridging role between these approaches by augmenting and modifying the main ideas of the "rational choice" model to make it more compatible with empirical findings in other fields. The resulting model is used to analyze three major unresolved issues in the developing world: the sources of a government''s economic ideology, the origins of ethnic group boundaries, and the relationship between modernization and violence. Addressing theoretical problems that cut across numerous disciplines, this work will be of interest to a diversity of theoretically-minded scholars. Sun-Ki Chai is Assistant Professor of Sociology, University of Arizona.

Social computing is concerned with the study of social behavior and social context based on computational systems. Behavioral modeling provides a representation of the social behavior, and allows for experimenting, scenario planning, and deep und- standing of behavior, patterns, and potential outcomes. The pervasive use of computer and Internet technologies by humans in everyday life provides an unprecedented en- ronment of various social activities that, due to the platforms under which they take place, generate large amounts of stored data as a by-product, often in systematically organized form. Social computing facilitates behavioral modeling in model building, analysis, pattern mining, and prediction. Numerous interdisciplinary and interdepe- ent systems are created and used to represent the various social and physical systems for investigating the interactions between groups, communities, or nation-states. This requires joint efforts to take advantage of the state-of-the-art research from multiple disciplines improving social computing and behavioral modeling in order to document lessons learned and develop novel theories, experiments, and methodologies to better explain the interaction between social (both informal and institutionalized), psyc- logical, and physical mechanisms. The goal is to enable us to experiment, create, and recreate an operational environment with a better understanding of the contributions from each individual discipline, forging joint interdisciplinary efforts. This volume comprises the proceedings of the third international workshop on - cial Computing, Behavioral Modeling and Prediction, which has grown trem- dously.

Social computing is concerned with the study of social behavior and social context based on computational systems. Behavioral modeling provides a representation of the social behavior, and allows for experimenting, scenario planning, and deep und- standing of behavior, patterns, and potential outcomes. The pervasive use of computer and Internet technologies by humans in everyday life provides an unprecedented en- ronment of various social activities that, due to the platforms under which they take place, generate large amounts of stored data as a by-product, often in systematically organized form. Social computing facilitates behavioral modeling in model building, analysis, pattern mining, and prediction. Numerous interdisciplinary and interdepe- ent systems are created and used to represent the various social and physical systems for investigating the interactions between groups, communities, or nation-states. This requires joint efforts to take advantage of the state-of-the-art research from multiple disciplines improving social computing and behavioral modeling in order to document lessons learned and develop novel theories, experiments, and methodologies to better explain the interaction between social (both informal and institutionalized), psyc- logical, and physical mechanisms. The goal is to enable us to experiment, create, and recreate an operational environment with a better understanding of the contributions from each individual discipline, forging joint interdisciplinary efforts. This volume comprises the proceedings of the third international workshop on - cial Computing, Behavioral Modeling and Prediction, which has grown trem- dously.

This book constitutes the refereed proceedings of the 4th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, held in College Park, MD, USA, March 29-31, 2011. The 48 papers and 3 keynotes presented in this volume were carefully reviewed and selected from 88 submissions. The papers cover a wide range of topics including social network analysis; modeling; machine learning and data mining; social behaviors; public health; cultural aspects; and effects and search.

Social science research is fragmented by the widely differing and seemingly contradictory approaches used by the different disciplines of the social sciences to explain human action. Attempts at integrating different social science approaches to explain action have often been frustrated by the difficulty of incorporating cultural assumptions into rational choice theories without robbing them of their generality or making them too vague for predictions. Another problem has been the major disagreements among cultural theorists regarding the ways in which culture affects preferences and beliefs. This book provides a general model of preference and belief formation, addressing the largest unresolved issue in rational choice theories of action. It attempts to play a bridging role between these approaches by augmenting and modifying the main ideas of the "rational choice" model to make it more compatible with empirical findings in other fields. The resulting model is used to analyze three major unresolved issues in the developing world: the sources of a government''s economic ideology, the origins of ethnic group boundaries, and the relationship between modernization and violence. Addressing theoretical problems that cut across numerous disciplines, this work will be of interest to a diversity of theoretically-minded scholars. Sun-Ki Chai is Assistant Professor of Sociology, University of Arizona.

Social computing is concerned with the study of social behavior and social context based on computational systems. Behavioral modeling provides a representation of the social behavior, and allows for experimenting, scenario planning, and deep und- standing of behavior, patterns, and potential outcomes. The pervasive use of computer and Internet technologies by humans in everyday life provides an unprecedented en- ronment of various social activities that, due to the platforms under which they take place, generate large amounts of stored data as a by-product, often in systematically organized form. Social computing facilitates behavioral modeling in model building, analysis, pattern mining, and prediction. Numerous interdisciplinary and interdepe- ent systems are created and used to represent the various social and physical systems for investigating the interactions between groups, communities, or nation-states. This requires joint efforts to take advantage of the state-of-the-art research from multiple disciplines improving social computing and behavioral modeling in order to document lessons learned and develop novel theories, experiments, and methodologies to better explain the interaction between social (both informal and institutionalized), psyc- logical, and physical mechanisms. The goal is to enable us to experiment, create, and recreate an operational environment with a better understanding of the contributions from each individual discipline, forging joint interdisciplinary efforts. This volume comprises the proceedings of the third international workshop on - cial Computing, Behavioral Modeling and Prediction, which has grown trem- dously.

Social computing is concerned with the study of social behavior and social context based on computational systems. Behavioral modeling provides a representation of the social behavior, and allows for experimenting, scenario planning, and deep und- standing of behavior, patterns, and potential outcomes. The pervasive use of computer and Internet technologies by humans in everyday life provides an unprecedented en- ronment of various social activities that, due to the platforms under which they take place, generate large amounts of stored data as a by-product, often in systematically organized form. Social computing facilitates behavioral modeling in model building, analysis, pattern mining, and prediction. Numerous interdisciplinary and interdepe- ent systems are created and used to represent the various social and physical systems for investigating the interactions between groups, communities, or nation-states. This requires joint efforts to take advantage of the state-of-the-art research from multiple disciplines improving social computing and behavioral modeling in order to document lessons learned and develop novel theories, experiments, and methodologies to better explain the interaction between social (both informal and institutionalized), psyc- logical, and physical mechanisms. The goal is to enable us to experiment, create, and recreate an operational environment with a better understanding of the contributions from each individual discipline, forging joint interdisciplinary efforts. This volume comprises the proceedings of the third international workshop on - cial Computing, Behavioral Modeling and Prediction, which has grown trem- dously.

This book constitutes the refereed proceedings of the 4th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, held in College Park, MD, USA, March 29-31, 2011. The 48 papers and 3 keynotes presented in this volume were carefully reviewed and selected from 88 submissions. The papers cover a wide range of topics including social network analysis; modeling; machine learning and data mining; social behaviors; public health; cultural aspects; and effects and search.