Mathematical Models For Social Psychology

This edited volume presents examples of social science research projects that employ new methods of quantitative analysis and mathematical modeling of social processes. This book presents the fascinating areas of empirical and theoretical investigations that use formal mathematics in a way that is accessible for individuals lacking extensive expertise but still desiring to expand their scope of research methodology and add to their data analysis toolbox. Mathematical Modeling of Social Relationships professes how mathematical modeling can help us understand the fundamental, compelling, and yet sometimes complicated concepts that arise in the social sciences. This volume will appeal to upper-level students and researchers in a broad area of fields within the social sciences, as well as the disciplines of social psychology, complex systems, and applied mathematics.

In this book Lee Rudolph brings together international contributors who combine psychological and mathematical perspectives to analyse how qualitative mathematics can be used to create models of social and psychological processes. Bridging the gap between the fields with an imaginative and stimulating collection of contributed chapters, the volume updates the current research on the subject, which until now has been rather limited, focussing largely on the use of statistics. Qualitative Mathematics for the Social Sciences contains a variety of useful illustrative figures, introducing readers from the social sciences to the rich contribution that modern mathematics has made to our knowledge of logic, structures, and dynamic systems. A beguiling array of conceptual systems, topological models and fractals are discussed which transcend the application of statistics, and bring a fresh perspective to the study of social representations. The wide selection of qualitative mathematical methodologies discussed in this volume will be hugely valuable to higher-level undergraduate and postgraduate students of psychology, sociology and mathematics. It will also be useful for researchers, academics and professionals from the social sciences who want a firmer grasp on the use of qualitative mathematics.

In this two volume festschrift, contributors explore the theoretical developments (Volume I) and applications (Volume II) in traditional cognitive psychology domains, and model other areas of human performance that benefit from rigorous mathematical approaches. It brings together former classmates, students and colleagues of Dr. James T. Townsend, a pioneering researcher in the field since the early 1960s, to provide a current overview of mathematical modeling in psychology. Townsend’s research critically emphasized a need for rigor in the practice of cognitive modeling, and for providing mathematical definition and structure to ill-defined psychological topics. The research captured demonstrates how the interplay of theory and application, bridged by rigorous mathematics, can move cognitive modeling forward.

Mathematical Models of Attitude Change, Volume 1: Change in Single Attitudes and Cognitive Structure presents the mathematical models that address the existing verbal attitude change theories, which are translated into families of mathematical models. This book discusses the two types of attitude change, namely, the attitude toward the object of the message and the attitude toward the source of the message. Organized into three parts encompassing 17 chapters, this volume begins with an overview of the mathematical models of attitude change that are derived from several theories. This text then explains the empirical work designed to test selected mathematical models of attitude change. Other chapters consider the predictions made by different models, including reinforcement, information processing, social judgment, balance, dissonance, and congruity. This book discusses as well the attitude-related variable, namely, belief and belief change. The final chapter deals with models of change in hierarchical organized attitudes using alternative theories of attitude change. This book is a valuable resource for psychologists.

Originally published in 1977, this volume was intended to provide a relatively elementary and clear overview of some of the more important approaches to social psychology at the time. There are a number of perspectives on this discipline, but here, instead of traditional theoretical approaches (e.g. field theory, role theory or S-R) the point of view is from the general perspective. The first chapter approaches social psychology as an experimental science, with the history and philosophic traditions discussed, as well as the current state of the field. Other chapters approach the discipline from the perspectives of symbolic interaction, social development, and ethology. The final chapter is devoted to the uses of mathematical models in social psychology. This volume was intended to serve as a helpful integration of the field, and will still be useful as a text in its historical context.

In this two volume festschrift, contributors explore the theoretical developments (Volume I) and applications (Volume II) in traditional cognitive psychology domains, and model other areas of human performance that benefit from rigorous mathematical approaches. It brings together former classmates, students and colleagues of Dr. James T. Townsend, a pioneering researcher in the field since the early 1960s, to provide a current overview of mathematical modeling in psychology. Townsend’s research critically emphasized a need for rigor in the practice of cognitive modeling, and for providing mathematical definition and structure to ill-defined psychological topics. The research captured demonstrates how the interplay of theory and application, bridged by rigorous mathematics, can move cognitive modeling forward.

Over the last several decades, mathematical models have become central to the study of social evolution, both in biology and the social sciences. But students in these disciplines often seriously lack the tools to understand them. A primer on behavioral modeling that includes both mathematics and evolutionary theory, Mathematical Models of Social Evolution aims to make the student and professional researcher in biology and the social sciences fully conversant in the language of the field. Teaching biological concepts from which models can be developed, Richard McElreath and Robert Boyd introduce readers to many of the typical mathematical tools that are used to analyze evolutionary models and end each chapter with a set of problems that draw upon these techniques. Mathematical Models of Social Evolution equips behaviorists and evolutionary biologists with the mathematical knowledge to truly understand the models on which their research depends. Ultimately, McElreath and Boyd’s goal is to impart the fundamental concepts that underlie modern biological understandings of the evolution of behavior so that readers will be able to more fully appreciate journal articles and scientific literature, and start building models of their own.

Originally published in 1977, this volume was intended to provide a relatively elementary and clear overview of some of the more important approaches to social psychology at the time. There are a number of perspectives on this discipline, but here, instead of traditional theoretical approaches (e.g. field theory, role theory or S-R) the point of view is from the general perspective. The first chapter approaches social psychology as an experimental science, with the history and philosophic traditions discussed, as well as the current state of the field. Other chapters approach the discipline from the perspectives of symbolic interaction, social development, and ethology. The final chapter is devoted to the uses of mathematical models in social psychology. This volume was intended to serve as a helpful integration of the field, and will still be useful as a text in its historical context.