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A Data Set of Synthetic Utterances for Computational Personality Analysis.
1Head, The Functor Lab, Department of Cognitive and Brain Science, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel. yneuman@bgu.ac.il.
This study introduces a novel dataset of synthetic utterances based on psychodynamic personality dimensions. This resource aids computational personality analysis and authentic digital persona creation.
Area of Science:
- Computational psychology
- Artificial intelligence in social sciences
Background:
- Current computational personality analysis predominantly uses the Big Five model.
- Psychodynamic approaches are underrepresented in computational research despite theoretical depth.
Purpose of the Study:
- To introduce a novel dataset of synthetic utterances grounded in psychodynamic personality theory.
- To facilitate computational studies of personality beyond the Big Five.
- To support the creation of authentic digital personas.
Main Methods:
- Generation of 4972 synthetic utterances using AI (GPT-4) based on psychodynamic dimensions (depressive, obsessive, paranoid, narcissistic, anti-social psychopathic).
- Dataset validation through 14 distinct tests.
Main Results:
- A validated dataset of synthetic utterances representing five psychodynamic personality dimensions.
- Demonstration of AI's capability to generate theoretically grounded personality data.
Conclusions:
- The dataset offers a valuable resource for advancing computational personality research.
- Potential applications include enhancing digital character authenticity in gaming and media.
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