Although neural network models have had a dramatic impact on the cognitive and brain sciences, social psychology has remained largely unaffected by this intellectual explosion. The first to apply neural network models to social phenomena, this book includes chapters by nearly all of the individuals currently working in this area. Bringing these various approaches together in one place, it allows readers to appreciate the breadth of these approaches, as well as the theoretical commonality of many of these models.
The contributors address a number of central issues in social psychology and show how these kinds of models provide insight into many classic issues. Many chapters hint that this approach provides the seeds of a theoretical integration that the field has lacked. Each chapter discusses an explicit connectionist model of a central problem in social psychology. Since many of the contributors either use a standard architecture or provide a computer program, interested readers, with a little work, should be able to implement their own variations of models.
Chapters are devoted to the following topics and models:
* the learning and application of social categories and stereotypes;
* causal reasoning, social explanation, and person perception;
* personality and social behavior;
* classic dissonance phenomena; and
* belief change and the coherence of large scale belief systems.
"On the whole, this book is a good 'first of its kind' in the field of social psychology. The main strong point is that it brings the data in the field to computational models. In places, these models are almost as good as the Rumelhart and McClelland classics in terms of their explanatory power."
—Journal of Artificial Societies & Social Simulation