A Connectionist Model of Person Perception and Stereotype Formation

  • Christophe L. Labiouse
  • Robert M. French
Conference paper
Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)


Connectionist modeling has begun to have an impact on research in social cognition. PDP models have been used to model a broad range of social psychological topics such as person perception, illusory correlations, cognitive dissonance, social categorization and stereotypes. Smith and DeCoster [28] recently proposed a recurrent connectionist model of person perception and stereotyping that accounts for a number of phenomena usually seen as contradictory or difficult to integrate into a single coherent conceptual framework. While their model is based on clearly defined and potentially far–reaching theoretical principles, it nonetheless suffers from certain shortcomings, among them, the use of misleading dependent measures and the incapacity of the network to develop its own internal representations. We propose an alternative connectionist model – an autoencoder – to overcome these limitations. In particular, the development of stereotypes within the context of this model will be discussed.


Hide Layer Social Cognition Cognitive Dissonance Error Score Connectionist Model 
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© Springer-Verlag London 2001

Authors and Affiliations

  • Christophe L. Labiouse
  • Robert M. French

There are no affiliations available

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