Lexical differences in autobiographical narratives from schizophrenic patients and healthy controls

Authors:
Kai Hong;Christian G. Kohler;Mary E. March;Amber A. Parker;Ani Nenkova
Affiliations:
University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA
Venue:
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Year:
2012

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Abstract

We present a system for automatic identification of schizophrenic patients and healthy controls based on narratives the subjects recounted about emotional experiences in their own life. The focus of the study is to identify the lexical features that distinguish the two populations. We report the results of feature selection experiments that demonstrate that the classifier can achieve accuracy on patient level prediction as high as 76.9% with only a small set of features. We provide an in-depth discussion of the lexical features that distinguish the two groups and the unexpected relationship between emotion types of the narratives and the accuracy of patient status prediction.