Personality Trait Detection using an Hierarchy of Tree-transformers and Graph Attention Network
by Sudipta Singha Roy, Robert Mercer, and Souvik Kundu
Published onJun 05, 2023
Personality Trait Detection using an Hierarchy of Tree-transformers and Graph Attention Network
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Abstract
Automatic personality trait detection from a person’s writings is helpful for professionals to assess the mental health of an individual, as well as helping individuals to determine their strengths and weaknesses for making choices such as personal improvement, workplace compatibility, and life-style decision-making. Psychologists have identified a set of personality traits that may be present in an individual’s personality. This work classifies the writings of an individual into a subset of these traits. The classifier model comprises an hierarchical structure of tree-transformers and a graph attention network (GAT). The tree-transformers encode the sentences and the following GAT layer encodes the complete text of an individual’s writing. Our model has shown a large performance boost over two benchmark corpora compared to previous works.
Creative Commons Attribution 4.0 International License (CC-BY 4.0)