Testing neural network models of personality |
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Authors: | Michael Quek D.S. Moskowitz |
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Affiliation: | Department of Psychology, McGill University, Stewart Biological Sciences Building, 1205 Dr. Penfield Avenue, Montreal, Que., Canada H3A1B1 |
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Abstract: | Attempts to develop neural network models of personality have not generally used empirical data for training and validating the models. Two illustrations are provided which demonstrate the incorporation of empirical data into the modeling of behavioral responses to situations varying in closeness and hierarchical role relationships. An event-contingent recording procedure is utilized to obtain data from the same participant in multiple events for multiple situations. This data is then used in the training and validation of the neural networks. The first illustration models dominant and submissive behaviors in response to situations varying in social role status. The second illustration models agreeable and quarrelsome behaviors in response to situations varying in closeness and gender of the interaction partner. The predictions from both neural network models are consistent with previous research. |
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Keywords: | Neural network models Agency Communion Interpersonal behavior Dominance Submissiveness Agreeableness Quarrelsomeness |
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